{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T18:13:25Z","timestamp":1791915205413,"version":"4.3.4"},"reference-count":125,"publisher":"Springer Science and Business Media LLC","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,19]]},"DOI":"10.7759\/cureus.56472","type":"journal-article","created":{"date-parts":[[2024,3,19]],"date-time":"2024-03-19T16:50:57Z","timestamp":1710867057000},"source":"Crossref","is-referenced-by-count":54,"title":["The Role of Artificial Intelligence in Identifying Depression and Anxiety: A Comprehensive Literature Review"],"prefix":"10.7759","author":[{"given":"Fabeha","family":"Zafar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laraib","family":"Fakhare Alam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rafael R","family":"Vivas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jada","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"See Jia","family":"Whei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sameer","family":"Mehmood","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amirali","family":"Sadeghzadegan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohit","family":"Lakkimsetti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zahra","family":"Nazir","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-6494.2004.00298.x","article-title":"Healthy and unhealthy emotion regulation: personality processes, individual differences, and life span development","volume":"72","author":"John OP","year":"2004","unstructured":"John OP, Gross JJ. Healthy and unhealthy emotion regulation: personality processes, individual differences, and life span development. J Pers. 2004, 72:1301-33. 10.1111\/j.1467-6494.2004.00298.x","journal-title":"J Pers"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2007.05.031","article-title":"The neural bases of emotion regulation: reappraisal and suppression of negative emotion","volume":"63","author":"Goldin PR","year":"2008","unstructured":"Goldin PR, McRae K, Ramel W, Gross JJ. The neural bases of emotion regulation: reappraisal and suppression of negative emotion. Biol Psychiatry. 2008, 63:577-86. 10.1016\/j.biopsych.2007.05.031","journal-title":"Biol Psychiatry"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0119500","article-title":"The neural correlates of emotion regulation by implementation intentions","volume":"10","author":"Hallam GP","year":"2015","unstructured":"Hallam GP, Webb TL, Sheeran P, et al.. The neural correlates of emotion regulation by implementation intentions. PLoS One. 2015, 10:e0119500. 10.1371\/journal.pone.0119500","journal-title":"PLoS One"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.5114\/nan.2017.68899","article-title":"Cognition, emotions, depression, inflammable processes-basic principles of the neurodevelopmental theory of depression","volume":"12","author":"Ga\u0142ecki P","year":"2017","unstructured":"Ga\u0142ecki P, Talarowska M. Cognition, emotions, depression, inflammable processes-basic principles of the neurodevelopmental theory of depression. Neuropsychologia. 2017, 12:30-7. 10.5114\/nan.2017.68899","journal-title":"Neuropsychologia"},{"key":"ref5","unstructured":"Depressive disorder (depression). (2023). Accessed. 03.31.2023: https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/depression."},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1111\/jcpp.12844","article-title":"Editorial: what is depression?","volume":"58","author":"Stringaris A","year":"2017","unstructured":"Stringaris A. Editorial: what is depression?. J Child Psychol Psychiatry. 2017, 58:1287-9. 10.1111\/jcpp.12844","journal-title":"J Child Psychol Psychiatry"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.2020.20030305","article-title":"The critical relationship between anxiety and depression","volume":"177","author":"Kalin NH","year":"2020","unstructured":"Kalin NH. The critical relationship between anxiety and depression. Am J Psychiatry. 2020, 177:365-7. 10.1176\/appi.ajp.2020.20030305","journal-title":"Am J Psychiatry"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1520-6394(1996)4:4<160::AID-DA2>3.0.CO;2-J","article-title":"Comorbid depression and anxiety spectrum disorders","volume":"4","author":"Gorman JM","year":"1996","unstructured":"Gorman JM. Comorbid depression and anxiety spectrum disorders. Depress Anxiety. 1996, 4:160-8. 10.1002\/(SICI)1520-6394(1996)4:4&lt;160::AID-DA2&gt;3.0.CO;2-J","journal-title":"Depress Anxiety"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s11920-019-1094-0","article-title":"Artificial intelligence for mental health and mental illnesses: an overview","volume":"21","author":"Graham S","year":"2019","unstructured":"Graham S, Depp C, Lee EE, Nebeker C, Tu X, Kim HC, Jeste DV. Artificial intelligence for mental health and mental illnesses: an overview. Curr Psychiatry Rep. 2019, 21:116. 10.1007\/s11920-019-1094-0","journal-title":"Curr Psychiatry Rep"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.2196\/26540","article-title":"Predicting depression from smartphone behavioral markers using machine learning methods, hyperparameter optimization, and feature importance analysis: exploratory study","volume":"9","author":"Opoku Asare K","year":"2021","unstructured":"Opoku Asare K, Terhorst Y, Vega J, Peltonen E, Lagerspetz E, Ferreira D. Predicting depression from smartphone behavioral markers using machine learning methods, hyperparameter optimization, and feature importance analysis: exploratory study. JMIR Mhealth Uhealth. 2021, 9:e26540. 10.2196\/26540","journal-title":"JMIR Mhealth Uhealth"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.copsyc.2020.04.005","article-title":"AI in mental health","volume":"36","author":"D'Alfonso S","year":"2020","unstructured":"D'Alfonso S. AI in mental health. Curr Opin Psychol. 2020, 36:112-7. 10.1016\/j.copsyc.2020.04.005","journal-title":"Curr Opin Psychol"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.2196\/42672","article-title":"Wearable artificial intelligence for anxiety and depression: scoping review","volume":"25","author":"Abd-Alrazaq A","year":"2023","unstructured":"Abd-Alrazaq A, AlSaad R, Aziz S, et al.. Wearable artificial intelligence for anxiety and depression: scoping review. J Med Internet Res. 2023, 25:e42672. 10.2196\/42672","journal-title":"J Med Internet Res"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-022-00631-8","article-title":"The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review","volume":"5","author":"Abd-Alrazaq A","year":"2022","unstructured":"Abd-Alrazaq A, Alhuwail D, Schneider J, et al.. The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review. NPJ Digit Med. 2022, 5:87. 10.1038\/s41746-022-00631-8","journal-title":"NPJ Digit Med"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s11920-022-01378-5","article-title":"Expectations for artificial intelligence (AI) in psychiatry","volume":"24","author":"Monteith S","year":"2022","unstructured":"Monteith S, Glenn T, Geddes J, Whybrow PC, Achtyes E, Bauer M. Expectations for artificial intelligence (AI) in psychiatry. Curr Psychiatry Rep. 2022, 24:709-21. 10.1007\/s11920-022-01378-5","journal-title":"Curr Psychiatry Rep"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpsc.2021.02.001","article-title":"Artificial intelligence for mental health care: clinical applications, barriers, facilitators, and artificial wisdom","volume":"6","author":"Lee EE","year":"2021","unstructured":"Lee EE, Torous J, De Choudhury M, et al.. Artificial intelligence for mental health care: clinical applications, barriers, facilitators, and artificial wisdom. Biol Psychiatry Cogn Neurosci Neuroimaging. 2021, 6:856-64. 10.1016\/j.bpsc.2021.02.001","journal-title":"Biol Psychiatry Cogn Neurosci Neuroimaging"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.2196\/16021","article-title":"Effectiveness and safety of using chatbots to improve mental health: systematic review and meta-analysis","volume":"22","author":"Abd-Alrazaq AA","year":"2020","unstructured":"Abd-Alrazaq AA, Rababeh A, Alajlani M, Bewick BM, Househ M. Effectiveness and safety of using chatbots to improve mental health: systematic review and meta-analysis. J Med Internet Res. 2020, 22:e16021. 10.2196\/16021","journal-title":"J Med Internet Res"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.4088\/JCP.13r08894","article-title":"A meta-analysis of computerized cognitive-behavioral therapy for the treatment of DSM-5 anxiety disorders","volume":"75","author":"Adelman CB","year":"2014","unstructured":"Adelman CB, Panza KE, Bartley CA, Bontempo A, Bloch MH. A meta-analysis of computerized cognitive-behavioral therapy for the treatment of DSM-5 anxiety disorders. J Clin Psychiatry. 2014, 75:e695-704. 10.4088\/JCP.13r08894","journal-title":"J Clin Psychiatry"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpsychires.2018.10.006","article-title":"A systematic review of the effectiveness of mobile apps for monitoring and management of mental health symptoms or disorders","volume":"107","author":"Wang K","year":"2018","unstructured":"Wang K, Varma DS, Prosperi M. A systematic review of the effectiveness of mobile apps for monitoring and management of mental health symptoms or disorders. J Psychiatr Res. 2018, 107:73-8. 10.1016\/j.jpsychires.2018.10.006","journal-title":"J Psychiatr Res"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1002\/med.21764","article-title":"Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: state-of-the-arts and future directions","volume":"41","author":"Vatansever S","year":"2021","unstructured":"Vatansever S, Schlessinger A, Wacker D, Kaniskan H\u00dc, Jin J, Zhou MM, Zhang B. Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: state-of-the-arts and future directions. Med Res Rev. 2021, 41:1427-73. 10.1002\/med.21764","journal-title":"Med Res Rev"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.matpr.2022.01.467","article-title":"Depression detection using emotional artificial intelligence and machine learning: a closer review","volume":"58","author":"Manju LJ","year":"2022","unstructured":"Manju LJ, Kanoongo N. Depression detection using emotional artificial intelligence and machine learning: a closer review. Mater Today Proc. 2022, 58:217-26. 10.1016\/j.matpr.2022.01.467","journal-title":"Mater Today Proc"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.2196\/26771","article-title":"Acceptability and effectiveness of artificial intelligence therapy for anxiety and depression (Youper): longitudinal observational study","volume":"23","author":"Mehta A","year":"2021","unstructured":"Mehta A, Niles AN, Vargas JH, Marafon T, Couto DD, Gross JJ. Acceptability and effectiveness of artificial intelligence therapy for anxiety and depression (Youper): longitudinal observational study. J Med Internet Res. 2021, 23:e26771. 10.2196\/26771","journal-title":"J Med Internet Res"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s13347-021-00450-x","article-title":"Four responsibility gaps with artificial intelligence: why they matter and how to address them","volume":"34","author":"Santoni de Sio F","year":"2021","unstructured":"Santoni de Sio F, Mecacci G. Four responsibility gaps with artificial intelligence: why they matter and how to address them. Philos Technol. 2021, 34:1057-84. 10.1007\/s13347-021-00450-x","journal-title":"Philos Technol"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2023-076193","article-title":"Sensitivity and specificity of the Patient Health Questionnaire (PHQ-9, PHQ-8, PHQ-2) and General Anxiety Disorder scale (GAD-7, GAD-2) for depression and anxiety diagnosis: a cross-sectional study in a Peruvian hospital population","volume":"13","author":"Villarreal-Zegarra D","year":"2023","unstructured":"Villarreal-Zegarra D, Barrera-Begazo J, Otaz\u00fa-Alfaro S, Mayo-Puchoc N, Bazo-Alvarez JC, Huarcaya-Victoria J. Sensitivity and specificity of the Patient Health Questionnaire (PHQ-9, PHQ-8, PHQ-2) and General Anxiety Disorder scale (GAD-7, GAD-2) for depression and anxiety diagnosis: a cross-sectional study in a Peruvian hospital population. BMJ Open. 2023, 13:e076193. 10.1136\/bmjopen-2023-076193","journal-title":"BMJ Open"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1097\/00004045-200203000-00006","article-title":"Assessing behavioral health using OASIS: Part 1: depression and suicidality","volume":"20","author":"Raue PJ","year":"2002","unstructured":"Raue PJ, Brown EL, Bruce ML. Assessing behavioral health using OASIS: Part 1: depression and suicidality. Home Healthc Nurse. 2002, 20:154-61. 10.1097\/00004045-200203000-00006","journal-title":"Home Healthc Nurse"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1519\/JPT.0b013e31828df26f","article-title":"Depression in older adults: screening and referral","volume":"37","author":"Vieira ER","year":"2014","unstructured":"Vieira ER, Brown E, Raue P. Depression in older adults: screening and referral. J Geriatr Phys Ther. 2014, 37:24-30. 10.1519\/JPT.0b013e31828df26f","journal-title":"J Geriatr Phys Ther"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1176\/appi.books.9780890425596","article-title":"","year":"2013","unstructured":"Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. American Psychiatric Association, Washington, DC; 2013. 10.1176\/appi.books.9780890425596"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2020.09.131","article-title":"Screening for depression in primary care with Patient Health Questionnaire-9 (PHQ-9): a systematic review","volume":"279","author":"Costantini L","year":"2021","unstructured":"Costantini L, Pasquarella C, Odone A, et al.. Screening for depression in primary care with Patient Health Questionnaire-9 (PHQ-9): a systematic review. J Affect Disord. 2021, 279:473-83. 10.1016\/j.jad.2020.09.131","journal-title":"J Affect Disord"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1001\/jama.282.18.1737","article-title":"Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study","volume":"282","author":"Spitzer RL","year":"1999","unstructured":"Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. JAMA. 1999, 282:1737-44. 10.1001\/jama.282.18.1737","journal-title":"JAMA"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1097\/01.MLR.0000093487.78664.3C","article-title":"The Patient Health Questionnaire-2: validity of a two-item depression screener","volume":"41","author":"Kroenke K","year":"2003","unstructured":"Kroenke K, Spitzer RL, Williams JB. The Patient Health Questionnaire-2: validity of a two-item depression screener. Med Care. 2003, 41:1284-92. 10.1097\/01.MLR.0000093487.78664.3C","journal-title":"Med Care"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.genhosppsych.2015.11.005","article-title":"Screening for anxiety disorders with the GAD-7 and GAD-2: a systematic review and diagnostic metaanalysis","volume":"39","author":"Plummer F","year":"2016","unstructured":"Plummer F, Manea L, Trepel D, McMillan D. Screening for anxiety disorders with the GAD-7 and GAD-2: a systematic review and diagnostic metaanalysis. Gen Hosp Psychiatry. 2016, 39:24-31. 10.1016\/j.genhosppsych.2015.11.005","journal-title":"Gen Hosp Psychiatry"},{"key":"ref31","article-title":"Generalized anxiety disorder and panic disorder in adults","volume":"106","author":"DeGeorge KC","year":"2022","unstructured":"DeGeorge KC, Grover M, Streeter GS. Generalized anxiety disorder and panic disorder in adults. Am Fam Physician. 2022, 106:157-64.","journal-title":"Am Fam Physician"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.jare.2022.08.021","article-title":"A hybrid explainable ensemble transformer encoder for pneumonia identification from chest X-ray images","volume":"48","author":"Ukwuoma CC","year":"2023","unstructured":"Ukwuoma CC, Qin Z, Belal Bin Heyat M, et al.. A hybrid explainable ensemble transformer encoder for pneumonia identification from chest X-ray images. J Adv Res. 2023, 48:191-211. 10.1016\/j.jare.2022.08.021","journal-title":"J Adv Res"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s40596-019-01025-x","article-title":"How to prepare prospective psychiatrists in the era of artificial intelligence","volume":"43","author":"Kim JW","year":"2019","unstructured":"Kim JW, Jones KL, D'Angelo E. How to prepare prospective psychiatrists in the era of artificial intelligence. Acad Psychiatry. 2019, 43:337-9. 10.1007\/s40596-019-01025-x","journal-title":"Acad Psychiatry"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.2196\/mental.7785","article-title":"Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully auto- mated conversational agent (woebot): a randomized controlled trial","volume":"4","author":"Fitzpatrick KK","year":"2017","unstructured":"Fitzpatrick KK, Darcy A, Vierhile M. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully auto- mated conversational agent (woebot): a randomized controlled trial. JMIR Ment Health. 2017, 4:e19. 10.2196\/mental.7785","journal-title":"JMIR Ment Health"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0057447","article-title":"The effectiveness of Internet cognitive behavioural therapy (iCBT) for depression in primary care: a quality assurance study","volume":"8","author":"Williams AD","year":"2013","unstructured":"Williams AD, Andrews G. The effectiveness of Internet cognitive behavioural therapy (iCBT) for depression in primary care: a quality assurance study. PLoS One. 2013, 8:e57447. 10.1371\/journal.pone.0057447","journal-title":"PLoS One"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1111\/eip.12332","article-title":"Derivation of a prediction model for a diagnosis of depression in young adults: a matched case-control study using electronic primary care records","volume":"12","author":"Nichols L","year":"2018","unstructured":"Nichols L, Ryan R, Connor C, Birchwood M, Marshall T. Derivation of a prediction model for a diagnosis of depression in young adults: a matched case-control study using electronic primary care records. Early Interv Psychiatry. 2018, 12:444-55. 10.1111\/eip.12332","journal-title":"Early Interv Psychiatry"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2021.738466","article-title":"Use of machine learning and artificial intelligence methods in geriatric mental health research involving electronic health record or administrative claims data: a systematic review","volume":"12","author":"Chowdhury M","year":"2021","unstructured":"Chowdhury M, Cervantes EG, Chan WY, Seitz DP. Use of machine learning and artificial intelligence methods in geriatric mental health research involving electronic health record or administrative claims data: a systematic review. Front Psychiatry. 2021, 12:738466. 10.3389\/fpsyt.2021.738466","journal-title":"Front Psychiatry"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwz189","article-title":"What is machine learning? A primer for the epidemiologist","volume":"188","author":"Bi Q","year":"2019","unstructured":"Bi Q, Goodman KE, Kaminsky J, Lessler J. What is machine learning? A primer for the epidemiologist. Am J Epidemiol. 2019, 188:2222-39. 10.1093\/aje\/kwz189","journal-title":"Am J Epidemiol"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s40273-019-00777-6","article-title":"Combining the power of artificial intelligence with the richness of healthcare claims data: opportunities and challenges","volume":"37","author":"Thesmar D","year":"2019","unstructured":"Thesmar D, Sraer D, Pinheiro L, Dadson N, Veliche R, Greenberg P. Combining the power of artificial intelligence with the richness of healthcare claims data: opportunities and challenges. Pharmacoeconomics. 2019, 37:745-52. 10.1007\/s40273-019-00777-6","journal-title":"Pharmacoeconomics"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-publhealth-040119-094437","article-title":"Machine learning in epidemiology and health outcomes research","volume":"41","author":"Wiemken TL","year":"2020","unstructured":"Wiemken TL, Kelley RR. Machine learning in epidemiology and health outcomes research. Annu Rev Public Health. 2020, 41:21-36. 10.1146\/annurev-publhealth-040119-094437","journal-title":"Annu Rev Public Health"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.5870","article-title":"Guidelines for developing and reporting machine learning predictive models in biomedical research: a multidisciplinary view","volume":"18","author":"Luo W","year":"2016","unstructured":"Luo W, Phung D, Tran T, et al.. Guidelines for developing and reporting machine learning predictive models in biomedical research: a multidisciplinary view. J Med Internet Res. 2016, 18:e323. 10.2196\/jmir.5870","journal-title":"J Med Internet Res"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3016782","article-title":"Implementation and use of disease diagnosis systems for electronic medical records based on machine learning: a complete review","volume":"8","author":"Latif J","year":"2020","unstructured":"Latif J, Xiao C, Tu S, Rehman S, Imran A, Bilal A. Implementation and use of disease diagnosis systems for electronic medical records based on machine learning: a complete review. IEEE Access. 2020, 8:150489-513. 10.1109\/ACCESS.2020.3016782","journal-title":"IEEE Access"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2019.21579","article-title":"Artificial intelligence in health care: a report from the National Academy of Medicine","volume":"323","author":"Matheny ME","year":"2020","unstructured":"Matheny ME, Whicher D, Thadaney Israni S. Artificial intelligence in health care: a report from the National Academy of Medicine. JAMA. 2020, 323:509-10. 10.1001\/jama.2019.21579","journal-title":"JAMA"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3398069","article-title":"Machine learning in mental health: a systematic review of the HCI literature to support the development of effective and implementable ML systems","volume":"27","author":"Thieme A","year":"2020","unstructured":"Thieme A, Belgrave D, Doherty G. Machine learning in mental health: a systematic review of the HCI literature to support the development of effective and implementable ML systems. ACM Trans Comput Hum Int. 2020, 27:1-53. 10.1145\/3398069","journal-title":"ACM Trans Comput Hum Int"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291719000151","article-title":"Machine learning in mental health: a scoping review of methods and applications","volume":"49","author":"Shatte AB","year":"2019","unstructured":"Shatte AB, Hutchinson DM, Teague SJ. Machine learning in mental health: a scoping review of methods and applications. Psychol Med. 2019, 49:1426-48. 10.1017\/S0033291719000151","journal-title":"Psychol Med"},{"key":"ref46","doi-asserted-by":"crossref","DOI":"10.1109\/ACCESS.2020.3029154","article-title":"Application of machine learning methods in mental health detection: a systematic review","volume":"8","author":"Rahman R","year":"2020","unstructured":"Rahman R, Al-Garadi MA. Application of machine learning methods in mental health detection: a systematic review. IEEE Access. 2020, 8:183952-64.","journal-title":"IEEE Access"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.3390\/healthcare11030285","article-title":"A review of machine learning and deep learning approaches on mental health diagnosis","volume":"11","author":"Iyortsuun NK","year":"2023","unstructured":"Iyortsuun NK, Kim SH, Jhon M, Yang HJ, Pant S. A review of machine learning and deep learning approaches on mental health diagnosis. Healthcare (Basel). 2023, 11:10.3390\/healthcare11030285","journal-title":"Healthcare (Basel)"},{"key":"ref48","article-title":"Recognizing depression from Twitter activity","author":"Tsugawa S","year":"2015","unstructured":"Tsugawa S, Kikuchi Y, Kishino F, Nakajima K, Itoh Y, Ohsaki H. Recognizing depression from Twitter activity. ACM Conf Hum Factors Comput Syst. 2015,","journal-title":"ACM Conf Hum Factors Comput Syst"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2016.12.003","article-title":"Stress level detection via OSN usage pattern and chronicity analysis: an OSINT threat intelligence module","volume":"69","author":"Kandias M","year":"2017","unstructured":"Kandias M, Gritzalis D, Stavrou V, Nikoloulis K. Stress level detection via OSN usage pattern and chronicity analysis: an OSINT threat intelligence module. Comput Secur. 2017, 69:3-17. 10.1016\/j.cose.2016.12.003","journal-title":"Comput Secur"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ISS1.2017.8389299","article-title":"Depression detection using emotion artificial intelligence","author":"Deshpande M","year":"2017","unstructured":"Deshpande M, Rao V\r\n. Depression detection using emotion artificial intelligence. Conf Intell Sustain Syst. 2017, 858-62. 10.1109\/ISS1.2017.8389299","journal-title":"Conf Intell Sustain Syst"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjmed.2019.01.017","article-title":"Artificial intelligence transforms the future of health care","volume":"132","author":"Noorbakhsh-Sabet N","year":"2019","unstructured":"Noorbakhsh-Sabet N, Zand R, Zhang Y, Abedi V. Artificial intelligence transforms the future of health care. Am J Med. 2019, 132:795-801. 10.1016\/j.amjmed.2019.01.017","journal-title":"Am J Med"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.2196\/15708","article-title":"Machine learning and natural language processing in mental health: systematic review","volume":"23","author":"Le Glaz A","year":"2021","unstructured":"Le Glaz A, Haralambous Y, Kim-Dufor DH, et al.. Machine learning and natural language processing in mental health: systematic review. J Med Internet Res. 2021, 23:e15708. 10.2196\/15708","journal-title":"J Med Internet Res"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1038\/s41398-023-02592-2","article-title":"Natural language processing for mental health interventions: a systematic review and research framework","volume":"13","author":"Malgaroli M","year":"2023","unstructured":"Malgaroli M, Hull TD, Zech JM, Althoff T. Natural language processing for mental health interventions: a systematic review and research framework. Transl Psychiatry. 2023, 13:309. 10.1038\/s41398-023-02592-2","journal-title":"Transl Psychiatry"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.patter.2022.100602","article-title":"Modern views of machine learning for precision psychiatry","volume":"3","author":"Chen ZS","year":"2022","unstructured":"Chen ZS, Kulkarni PP, Galatzer-Levy IR, Bigio B, Nasca C, Zhang Y. Modern views of machine learning for precision psychiatry. Patterns (N Y). 2022, 3:100602. 10.1016\/j.patter.2022.100602","journal-title":"Patterns (N Y)"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.3389\/fdgth.2021.779091","article-title":"Listening to mental health crisis needs at scale: using natural language processing to understand and evaluate a mental health crisis text messaging service","volume":"3","author":"Liu Z","year":"2021","unstructured":"Liu Z, Peach RL, Lawrance EL, Noble A, Ungless MA, Barahona M. Listening to mental health crisis needs at scale: using natural language processing to understand and evaluate a mental health crisis text messaging service. Front Digit Health. 2021, 3:779091. 10.3389\/fdgth.2021.779091","journal-title":"Front Digit Health"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/s41870-022-00999-6","article-title":"Mental healthcare chatbot based on natural language processing and deep learning approaches: Ted the therapist","volume":"14","author":"Chi NT","year":"2022","unstructured":"Chi NT. Mental healthcare chatbot based on natural language processing and deep learning approaches: Ted the therapist. Int J Inf Technol. 2022, 14:3757-66. 10.1007\/s41870-022-00999-6","journal-title":"Int J Inf Technol"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/s11245-023-09932-3","article-title":"Is AI the future of mental healthcare?","volume":"42","author":"Minerva F","year":"2023","unstructured":"Minerva F, Giubilini A. Is AI the future of mental healthcare?. Topoi (Dordr). 2023, 42:1-9. 10.1007\/s11245-023-09932-3","journal-title":"Topoi (Dordr)"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-022-00589-7","article-title":"Natural language processing applied to mental illness detection: a narrative review","volume":"5","author":"Zhang T","year":"2022","unstructured":"Zhang T, Schoene AM, Ji S, Ananiadou S. Natural language processing applied to mental illness detection: a narrative review. NPJ Digit Med. 2022, 5:46. 10.1038\/s41746-022-00589-7","journal-title":"NPJ Digit Med"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0240376","article-title":"Artificial intelligence in mental health and the biases of language based models","volume":"15","author":"Straw I","year":"2020","unstructured":"Straw I, Callison-Burch C. Artificial intelligence in mental health and the biases of language based models. PLoS One. 2020, 15:e0240376. 10.1371\/journal.pone.0240376","journal-title":"PLoS One"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2019.103978","article-title":"An overview of the features of chatbots in mental health: a scoping review","volume":"132","author":"Abd-Alrazaq AA","year":"2019","unstructured":"Abd-Alrazaq AA, Alajlani M, Alalwan AA, Bewick BM, Gardner P, Househ M. An overview of the features of chatbots in mental health: a scoping review. Int J Med Inform. 2019, 132:103978. 10.1016\/j.ijmedinf.2019.103978","journal-title":"Int J Med Inform"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.2196\/13216","article-title":"Your robot therapist will see you now: ethical implications of embodied artificial intelligence in psychiatry, psychology, and psychotherapy","volume":"21","author":"Fiske A","year":"2019","unstructured":"Fiske A, Henningsen P, Buyx A. Your robot therapist will see you now: ethical implications of embodied artificial intelligence in psychiatry, psychology, and psychotherapy. J Med Internet Res. 2019, 21:e13216. 10.2196\/13216","journal-title":"J Med Internet Res"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ICICCT.2018.8472986","article-title":"Digital psychiatry-curbing depression using therapy chatbot and depression analysis","author":"Sharma B","year":"2018","unstructured":"Sharma B, Puri H, Rawat D. Digital psychiatry-curbing depression using therapy chatbot and depression analysis. IEEE. 2018, 627-31. 10.1109\/ICICCT.2018.8472986","journal-title":"IEEE"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ICICCT.2017.7975195","article-title":"A novel approach for medical assistance using trained chatbot","author":"Madhu D","year":"2017","unstructured":"Madhu D, Jain C, Sebastain E, et al.. A novel approach for medical assistance using trained chatbot. ICICCT. 2017, 243-6. 10.1109\/ICICCT.2017.7975195","journal-title":"ICICCT"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1001\/jamainternmed.2023.1838","article-title":"Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum","volume":"183","author":"Ayers JW","year":"2023","unstructured":"Ayers JW, Poliak A, Dredze M, et al.. Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum. JAMA Intern Med. 2023, 183:589-96. 10.1001\/jamainternmed.2023.1838","journal-title":"JAMA Intern Med"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-67303-1_10","article-title":"Artificial intelligence for chatbots in mental health: opportunities and challenges","author":"Denecke K","year":"2021","unstructured":"Denecke K, Abd-Alrazaq A, Househ M. Artificial intelligence for chatbots in mental health: opportunities and challenges. Multiple Perspective Artificial Intelligence Healthcare. 2021. 10.1007\/978-3-030-67303-1_10"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.2196\/24087","article-title":"Use of telehealth during the COVID-19 pandemic: scoping review","volume":"22","author":"Doraiswamy S","year":"2020","unstructured":"Doraiswamy S, Abraham A, Mamtani R, Cheema S. Use of telehealth during the COVID-19 pandemic: scoping review. J Med Internet Res. 2020, 22:e24087. 10.2196\/24087","journal-title":"J Med Internet Res"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/s11126-022-09973-8","article-title":"Artificial intelligence and chatbots in psychiatry","volume":"93","author":"Pham KT","year":"2022","unstructured":"Pham KT, Nabizadeh A, Selek S. Artificial intelligence and chatbots in psychiatry. Psychiatr Q. 2022, 93:249-53. 10.1007\/s11126-022-09973-8","journal-title":"Psychiatr Q"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1186\/s13063-021-05301-w","article-title":"Optimising AVATAR therapy for people who hear distressing voices: study protocol for the AVATAR2 multi-centre randomised controlled trial","volume":"22","author":"Garety P","year":"2021","unstructured":"Garety P, Edwards CJ, Ward T, et al.. Optimising AVATAR therapy for people who hear distressing voices: study protocol for the AVATAR2 multi-centre randomised controlled trial. Trials. 2021, 22:366. 10.1186\/s13063-021-05301-w","journal-title":"Trials"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.2196\/33560","article-title":"Use of mobile and wearable artificial intelligence in child and adolescent psychiatry: scoping review","volume":"24","author":"Welch V","year":"2022","unstructured":"Welch V, Wy TJ, Ligezka A, Hassett LC, Croarkin PE, Athreya AP, Romanowicz M. Use of mobile and wearable artificial intelligence in child and adolescent psychiatry: scoping review. J Med Internet Res. 2022, 24:e33560. 10.2196\/33560","journal-title":"J Med Internet Res"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.3390\/brainsci9030050","article-title":"Assessing anxiety disorders using wearable devices: challenges and future directions","volume":"9","author":"Elgendi M","year":"2019","unstructured":"Elgendi M, Menon C. Assessing anxiety disorders using wearable devices: challenges and future directions. Brain Sci. 2019, 9:10.3390\/brainsci9030050","journal-title":"Brain Sci"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2019.11.156","article-title":"Mobile and wearable technology for monitoring depressive symptoms in children and adolescents: a scoping review","volume":"265","author":"Sequeira L","year":"2020","unstructured":"Sequeira L, Perrotta S, LaGrassa J, et al.. Mobile and wearable technology for monitoring depressive symptoms in children and adolescents: a scoping review. J Affect Disord. 2020, 265:314-24. 10.1016\/j.jad.2019.11.156","journal-title":"J Affect Disord"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(12)61689-4","article-title":"Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010","volume":"380","author":"Murray CJ","year":"2012","unstructured":"Murray CJ, Vos T, Lozano R, et al.. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012, 380:2197-223. 10.1016\/S0140-6736(12)61689-4","journal-title":"Lancet"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1192\/s2056474000001240","article-title":"Brain drain: a challenge to global mental health","volume":"13","author":"Oladeji BD","year":"2016","unstructured":"Oladeji BD, Gureje O. Brain drain: a challenge to global mental health. BJPsych Int. 2016, 13:61-3. 10.1192\/s2056474000001240","journal-title":"BJPsych Int"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2021.672347","article-title":"Current advances in wearable devices and their sensors in patients with depression","volume":"12","author":"Lee S","year":"2021","unstructured":"Lee S, Kim H, Park MJ, Jeon HJ. Current advances in wearable devices and their sensors in patients with depression. Front Psychiatry. 2021, 12:672347. 10.3389\/fpsyt.2021.672347","journal-title":"Front Psychiatry"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.3390\/s22030994","article-title":"Wearable sensing systems for monitoring mental health","volume":"22","author":"Kang M","year":"2022","unstructured":"Kang M, Chai K. Wearable sensing systems for monitoring mental health. Sensors (Basel). 2022, 22:10.3390\/s22030994","journal-title":"Sensors (Basel)"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1002\/jclp.22934","article-title":"Perceived acceptability of wearable devices for the treatment of mental health problems","volume":"76","author":"Hunkin H","year":"2020","unstructured":"Hunkin H, King DL, Zajac IT. Perceived acceptability of wearable devices for the treatment of mental health problems. J Clin Psychol. 2020, 76:987-1003. 10.1002\/jclp.22934","journal-title":"J Clin Psychol"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph16204051","article-title":"Relationship between physical activity level and depression of elderly people living alone","volume":"16","author":"Byeon H","year":"2019","unstructured":"Byeon H. Relationship between physical activity level and depression of elderly people living alone. Int J Environ Res Public Health. 2019, 16:10.3390\/ijerph16204051","journal-title":"Int J Environ Res Public Health"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-021-10684-1","article-title":"Correction to: Reduced level of physical activity during COVID-19 pandemic is associated with depression and anxiety levels: an internet-based survey","volume":"21","author":"Puccinelli PJ","year":"2021","unstructured":"Puccinelli PJ, da Costa TS, Seffrin A, et al.. Correction to: Reduced level of physical activity during COVID-19 pandemic is associated with depression and anxiety levels: an internet-based survey. BMC Public Health. 2021, 21:613. 10.1186\/s12889-021-10684-1","journal-title":"BMC Public Health"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2013.01.035","article-title":"Relationship between physical activity and depression and anxiety symptoms: a population study","volume":"149","author":"De Mello MT","year":"2013","unstructured":"De Mello MT, Lemos Vde A, Antunes HK, Bittencourt L, Santos-Silva R, Tufik S. Relationship between physical activity and depression and anxiety symptoms: a population study. J Affect Disord. 2013, 149:241-6. 10.1016\/j.jad.2013.01.035","journal-title":"J Affect Disord"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1016\/0165-1781(94)90122-8","article-title":"Circadian pattern of motor activity in major depressed patients undergoing antidepressant therapy: relationship between actigraphic measures and clinical course","volume":"52","author":"Raoux N","year":"1994","unstructured":"Raoux N, Benoit O, Dantchev N, et al.. Circadian pattern of motor activity in major depressed patients undergoing antidepressant therapy: relationship between actigraphic measures and clinical course. Psychiatry Res. 1994, 52:85-98. 10.1016\/0165-1781(94)90122-8","journal-title":"Psychiatry Res"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1016\/j.ypmed.2011.07.013","article-title":"Associations of objectively-assessed physical activity and sedentary time with depression: NHANES (2005-2006)","volume":"53","author":"Vallance JK","year":"2011","unstructured":"Vallance JK, Winkler EA, Gardiner PA, Healy GN, Lynch BM, Owen N. Associations of objectively-assessed physical activity and sedentary time with depression: NHANES (2005-2006). Prev Med. 2011, 53:284-8. 10.1016\/j.ypmed.2011.07.013","journal-title":"Prev Med"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1016\/j.smrv.2014.03.006","article-title":"A meta-analysis and model of the relationship between sleep and depression in adolescents: recommendations for future research and clinical practice","volume":"18","author":"Lovato N","year":"2014","unstructured":"Lovato N, Gradisar M. A meta-analysis and model of the relationship between sleep and depression in adolescents: recommendations for future research and clinical practice. Sleep Med Rev. 2014, 18:521-9. 10.1016\/j.smrv.2014.03.006","journal-title":"Sleep Med Rev"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpsychires.2009.01.009","article-title":"Relationship of anxiety disorders, sleep quality, and functional impairment in a community sample","volume":"43","author":"Ramsawh HJ","year":"2009","unstructured":"Ramsawh HJ, Stein MB, Belik SL, Jacobi F, Sareen J. Relationship of anxiety disorders, sleep quality, and functional impairment in a community sample. J Psychiatr Res. 2009, 43:926-33. 10.1016\/j.jpsychires.2009.01.009","journal-title":"J Psychiatr Res"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2009.12.012","article-title":"Impact of depression and antidepressant treatment on heart rate variability: a review and meta-analysis","volume":"67","author":"Kemp AH","year":"2010","unstructured":"Kemp AH, Quintana DS, Gray MA, Felmingham KL, Brown K, Gatt JM. Impact of depression and antidepressant treatment on heart rate variability: a review and meta-analysis. Biol Psychiatry. 2010, 67:1067-74. 10.1016\/j.biopsych.2009.12.012","journal-title":"Biol Psychiatry"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.3949\/ccjm.76.s2.03","article-title":"Depression and heart rate variability in patients with coronary heart disease","volume":"76 Suppl 2","author":"Carney RM","year":"2009","unstructured":"Carney RM, Freedland KE. Depression and heart rate variability in patients with coronary heart disease. Cleve Clin J Med. 2009, 76 Suppl 2:S13-7. 10.3949\/ccjm.76.s2.03","journal-title":"Cleve Clin J Med"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2014.00080","article-title":"Anxiety disorders are associated with reduced heart rate variability: a meta-analysis","volume":"5","author":"Chalmers JA","year":"2014","unstructured":"Chalmers JA, Quintana DS, Abbott MJ, Kemp AH. Anxiety disorders are associated with reduced heart rate variability: a meta-analysis. Front Psychiatry. 2014, 5:80. 10.3389\/fpsyt.2014.00080","journal-title":"Front Psychiatry"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2020.e03274","article-title":"Evaluating depression with multimodal wristband-type wearable device: screening and assessing patient severity utilizing machine-learning","volume":"6","author":"Tazawa Y","year":"2020","unstructured":"Tazawa Y, Liang KC, Yoshimura M, et al.. Evaluating depression with multimodal wristband-type wearable device: screening and assessing patient severity utilizing machine-learning. Heliyon. 2020, 6:e03274. 10.1016\/j.heliyon.2020.e03274","journal-title":"Heliyon"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1159\/000070579","article-title":"Depressed patients have higher body temperature: 5-HT transporter long promoter region effects","volume":"47","author":"Rausch JL","year":"2003","unstructured":"Rausch JL, Johnson ME, Corley KM, et al.. Depressed patients have higher body temperature: 5-HT transporter long promoter region effects. Neuropsychobiology. 2003, 47:120-7. 10.1159\/000070579","journal-title":"Neuropsychobiology"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.1838","article-title":"Harnessing context sensing to develop a mobile intervention for depression","volume":"13","author":"Burns MN","year":"2011","unstructured":"Burns MN, Begale M, Duffecy J, Gergle D, Karr CJ, Giangrande E, Mohr DC. Harnessing context sensing to develop a mobile intervention for depression. J Med Internet Res. 2011, 13:e55. 10.2196\/jmir.1838","journal-title":"J Med Internet Res"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1007\/s11920-019-1074-4","article-title":"The future of digital psychiatry","volume":"21","author":"Hariman K","year":"2019","unstructured":"Hariman K, Ventriglio A, Bhugra D. The future of digital psychiatry. Curr Psychiatry Rep. 2019, 21:88. 10.1007\/s11920-019-1074-4","journal-title":"Curr Psychiatry Rep"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0117785","article-title":"Hippocampal subfield volumes in first episode and chronic schizophrenia","volume":"10","author":"Kawano M","year":"2015","unstructured":"Kawano M, Sawada K, Shimodera S, et al.. Hippocampal subfield volumes in first episode and chronic schizophrenia. PLoS One. 2015, 10:e0117785. 10.1371\/journal.pone.0117785","journal-title":"PLoS One"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1002\/da.22014","article-title":"Aberrant amygdala-frontal cortex connectivity during perception of fearful faces and at rest in generalized social anxiety disorder","volume":"30","author":"Prater KE","year":"2013","unstructured":"Prater KE, Hosanagar A, Klumpp H, Angstadt M, Phan KL. Aberrant amygdala-frontal cortex connectivity during perception of fearful faces and at rest in generalized social anxiety disorder. Depress Anxiety. 2013, 30:234-41. 10.1002\/da.22014","journal-title":"Depress Anxiety"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13142323","article-title":"Machine learning to classify bipolar and unipolar depression using fMRI data: a systematic review and multivariate pattern analysis","volume":"13","author":"Yadav SK","year":"2023","unstructured":"Yadav SK, Gothe MP, Haslem LA, et al.. Machine learning to classify bipolar and unipolar depression using fMRI data: a systematic review and multivariate pattern analysis. NeuroImage. 2023, 13:2323. 10.3390\/diagnostics13142323","journal-title":"NeuroImage"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1002\/jclp.22680","article-title":"The impact of accommodating client preference in psychotherapy: a meta-analysis","volume":"74","author":"Swift JK","year":"2018","unstructured":"Swift JK, Callahan JL, Cooper M, Parkin SR. The impact of accommodating client preference in psychotherapy: a meta-analysis. J Clin Psychol. 2018, 74:1924-37. 10.1002\/jclp.22680","journal-title":"J Clin Psychol"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1002\/da.22646","article-title":"Sensing behavioral symptoms of mental health and delivering personalized interventions using mobile technologies","volume":"34","author":"Aung MH","year":"2017","unstructured":"Aung MH, Matthews M, Choudhury T. Sensing behavioral symptoms of mental health and delivering personalized interventions using mobile technologies. Depress Anxiety. 2017, 34:603-9. 10.1002\/da.22646","journal-title":"Depress Anxiety"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1007\/s11606-013-2455-8","article-title":"Bringing big data to personalized healthcare: a patient-centered framework","volume":"28 Suppl 3","author":"Chawla NV","year":"2013","unstructured":"Chawla NV, Davis DA. Bringing big data to personalized healthcare: a patient-centered framework. J Gen Intern Med. 2013, 28 Suppl 3:S660-5. 10.1007\/s11606-013-2455-8","journal-title":"J Gen Intern Med"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1002\/da.22302","article-title":"Internet psychotherapy and the future of personalized treatment","volume":"31","author":"Andrews G","year":"2014","unstructured":"Andrews G, Williams AD. Internet psychotherapy and the future of personalized treatment. Depress Anxiety. 2014, 31:912-5. 10.1002\/da.22302","journal-title":"Depress Anxiety"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-32-9271-0_12","article-title":"Individualized treatment strategy for depressive disorder","volume":"1180","author":"Chen J","year":"2019","unstructured":"Chen J, Hu S. Individualized treatment strategy for depressive disorder. Adv Exp Med Biol. 2019, 1180:219-32. 10.1007\/978-981-32-9271-0_12","journal-title":"Adv Exp Med Biol"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2021.106319","article-title":"Introduction of digital therapeutics","volume":"209","author":"Hong JS","year":"2021","unstructured":"Hong JS, Wasden C, Han DH. Introduction of digital therapeutics. Comput Methods Programs Biomed. 2021, 209:106319. 10.1016\/j.cmpb.2021.106319","journal-title":"Comput Methods Programs Biomed"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1016\/j.bushor.2015.03.006","article-title":"Is it all a game? Understanding the principles of gamification","volume":"58","author":"Robson K","year":"2015","unstructured":"Robson K, Plangger K, Kietzmann J, et al.. Is it all a game? Understanding the principles of gamification. ISSN. 2015, 58:411-20. 10.1016\/j.bushor.2015.03.006","journal-title":"ISSN"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1007\/s10488-012-0424-x","article-title":"Mobile technologies among people with serious mental illness: opportunities for future services","volume":"40","author":"Ben-Zeev D","year":"2013","unstructured":"Ben-Zeev D, Davis KE, Kaiser S, Krzsos I, Drake RE. Mobile technologies among people with serious mental illness: opportunities for future services. Adm Policy Ment Health. 2013, 40:340-3. 10.1007\/s10488-012-0424-x","journal-title":"Adm Policy Ment Health"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1016\/j.psychres.2017.06.081","article-title":"Effectiveness of an individually-tailored computerised CBT programme (Deprexis) for depression: a meta-analysis","volume":"256","author":"Twomey C","year":"2017","unstructured":"Twomey C, O'Reilly G, Meyer B. Effectiveness of an individually-tailored computerised CBT programme (Deprexis) for depression: a meta-analysis. Psychiatry Res. 2017, 256:371-7. 10.1016\/j.psychres.2017.06.081","journal-title":"Psychiatry Res"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.1016\/j.brat.2019.103440","article-title":"Symptom-specific effectiveness of an internet-based intervention in the treatment of mild to moderate depressive symptomatology: the potential of network estimation techniques","volume":"122","author":"Boschloo L","year":"2019","unstructured":"Boschloo L, Cuijpers P, Karyotaki E, Berger T, Moritz S, Meyer B, Klein JP. Symptom-specific effectiveness of an internet-based intervention in the treatment of mild to moderate depressive symptomatology: the potential of network estimation techniques. Behav Res Ther. 2019, 122:103440. 10.1016\/j.brat.2019.103440","journal-title":"Behav Res Ther"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.4861","article-title":"Effectiveness of a web-based guided self-help intervention for outpatients with a depressive disorder: short-term results from a randomized controlled trial","volume":"18","author":"Kenter RM","year":"2016","unstructured":"Kenter RM, Cuijpers P, Beekman A, van Straten A. Effectiveness of a web-based guided self-help intervention for outpatients with a depressive disorder: short-term results from a randomized controlled trial. J Med Internet Res. 2016, 18:e80. 10.2196\/jmir.4861","journal-title":"J Med Internet Res"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1080\/15228830802094429","article-title":"A comprehensive review and a meta-analysis of the effectiveness of Internet-based psychotherapeutic interventions","volume":"26","author":"Barak A","year":"2008","unstructured":"Barak A, Herbst LH, Nissim MB, et al.. A comprehensive review and a meta-analysis of the effectiveness of Internet-based psychotherapeutic interventions. J Technol Hum Serv. 2008, 26:109-60. 10.1080\/15228830802094429","journal-title":"J Technol Hum Serv"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.4.3.e17","article-title":"Issues in evaluating health websites in an Internet-based randomized controlled trial","volume":"4","author":"Eysenbach G","year":"2002","unstructured":"Eysenbach G. Issues in evaluating health websites in an Internet-based randomized controlled trial. J Med Internet Res. 2002, 4:E17. 10.2196\/jmir.4.3.e17","journal-title":"J Med Internet Res"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.5144\/0256-4947.2004.221","article-title":"Adherence to long-term therapies evidence for action","volume":"24","author":"Chaudri NA","year":"2004","unstructured":"Chaudri NA. Adherence to long-term therapies evidence for action. Ann Saudi Med. 2004, 24:221-2. 10.5144\/0256-4947.2004.221","journal-title":"Ann Saudi Med"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.1111\/j.1524-4733.2007.00213.x","article-title":"Medication compliance and persistence: terminology and definitions","volume":"11","author":"Cramer JA","year":"2008","unstructured":"Cramer JA, Roy A, Burrell A, Fairchild CJ, Fuldeore MJ, Ollendorf DA, Wong PK. Medication compliance and persistence: terminology and definitions. Value Health. 2008, 11:44-7. 10.1111\/j.1524-4733.2007.00213.x","journal-title":"Value Health"},{"key":"ref109","article-title":"The relationship between homework compliance and treatment outcomes among older adult outpatients with mild-to-moderate depression","volume":"11","author":"Coon DW","year":"2003","unstructured":"Coon DW, Thompson LW. The relationship between homework compliance and treatment outcomes among older adult outpatients with mild-to-moderate depression. Am J Geriatr Psychiatry. 2003, 11:53-61.","journal-title":"Am J Geriatr Psychiatry"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1016\/j.pec.2004.09.008","article-title":"Establishing the computer-patient working alliance in automated health behavior change interventions","volume":"59","author":"Bickmore T","year":"2005","unstructured":"Bickmore T, Gruber A, Picard R. Establishing the computer-patient working alliance in automated health behavior change interventions. Patient Educ Couns. 2005, 59:21-30. 10.1016\/j.pec.2004.09.008","journal-title":"Patient Educ Couns"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.7.2.e16","article-title":"Overcoming Depression on the Internet (ODIN) (2): a randomized trial of a self-help depression skills program with reminders","volume":"7","author":"Clarke G","year":"2005","unstructured":"Clarke G, Eubanks D, Reid E, et al.. Overcoming Depression on the Internet (ODIN) (2): a randomized trial of a self-help depression skills program with reminders. J Med Internet Res. 2005, 7:e16. 10.2196\/jmir.7.2.e16","journal-title":"J Med Internet Res"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.1772","article-title":"A systematic review of the impact of adherence on the effectiveness of e-therapies","volume":"13","author":"Donkin L","year":"2011","unstructured":"Donkin L, Christensen H, Naismith SL, Neal B, Hickie IB, Glozier N. A systematic review of the impact of adherence on the effectiveness of e-therapies. J Med Internet Res. 2011, 13:e52. 10.2196\/jmir.1772","journal-title":"J Med Internet Res"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.2147\/NDT.S337814","article-title":"From personalized medicine to precision psychiatry?","volume":"17","author":"\u010ce\u0161kov\u00e1 E","year":"2021","unstructured":"\u010ce\u0161kov\u00e1 E, \u0160ilh\u00e1n P. From personalized medicine to precision psychiatry?. Neuropsychiatr Dis Treat. 2021, 17:3663-8. 10.2147\/NDT.S337814","journal-title":"Neuropsychiatr Dis Treat"},{"key":"ref114","article-title":"World Mental Health Report 2022: Transforming Mental Health for All","year":"2022","unstructured":"World Mental Health Report 2022. Transforming Mental Health for All. World Health Organization, Geneva; 2022."},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1186\/s12910-021-00577-8","article-title":"Artificial intelligence for good health: a scoping review of the ethics literature","volume":"22","author":"Murphy K","year":"2021","unstructured":"Murphy K, Di Ruggiero E, Upshur R, et al.. Artificial intelligence for good health: a scoping review of the ethics literature. BMC Med Ethics. 2021, 22:14. 10.1186\/s12910-021-00577-8","journal-title":"BMC Med Ethics"},{"key":"ref116","doi-asserted-by":"publisher","DOI":"10.2196\/22269","article-title":"Ethical issues in patient data ownership","volume":"10","author":"Chiruvella V","year":"2021","unstructured":"Chiruvella V, Guddati AK. Ethical issues in patient data ownership. Interact J Med Res. 2021, 10:e22269. 10.2196\/22269","journal-title":"Interact J Med Res"},{"key":"ref117","article-title":"Opportunities, applications, challenges and ethical implications of artificial intelligence in psychiatry: a narrative review","volume":"80","author":"Terra M","year":"2023","unstructured":"Terra M, Baklola M, Ali S, et al.. Opportunities, applications, challenges and ethical implications of artificial intelligence in psychiatry: a narrative review. Egypt J Neurol Psychiatry Neurosurg. 2023, 80:1-10.","journal-title":"Egypt J Neurol Psychiatry Neurosurg"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1080\/15265161.2020.1819469","article-title":"Identifying ethical considerations for machine learning healthcare applications","volume":"20","author":"Char DS","year":"2020","unstructured":"Char DS, Abr\u00e0moff MD, Feudtner C. Identifying ethical considerations for machine learning healthcare applications. Am J Bioeth. 2020, 20:7-17. 10.1080\/15265161.2020.1819469","journal-title":"Am J Bioeth"},{"key":"ref119","doi-asserted-by":"publisher","DOI":"10.1192\/bjp.2019.245","article-title":"Will artificial intelligence eventually replace psychiatrists?","volume":"218","author":"Brown C","year":"2021","unstructured":"Brown C, Story GW, Mour\u00e3o-Miranda J, Baker JT. Will artificial intelligence eventually replace psychiatrists?. Br J Psychiatry. 2021, 218:131-4. 10.1192\/bjp.2019.245","journal-title":"Br J Psychiatry"},{"key":"ref120","doi-asserted-by":"publisher","DOI":"10.1177\/1178222619829083","article-title":"Can your phone be your therapist? Young people\u2019s ethical perspectives on the use of fully automated conversational agents (Chatbots) in mental health support","volume":"11","author":"Kretzschmar K","year":"2019","unstructured":"Kretzschmar K, Tyroll H, Pavarini G, Manzini A, Singh I. Can your phone be your therapist? Young people\u2019s ethical perspectives on the use of fully automated conversational agents (Chatbots) in mental health support. Biomed Inform Insights. 2019, 11:1178222619829083. 10.1177\/1178222619829083","journal-title":"Biomed Inform Insights"},{"key":"ref121","doi-asserted-by":"publisher","DOI":"10.4103\/jehp.jehp_402_23","article-title":"Addressing the challenges of AI-based telemedicine: best practices and lessons learned","volume":"12","author":"Sharma S","year":"2023","unstructured":"Sharma S, Rawal R, Shah D. Addressing the challenges of AI-based telemedicine: best practices and lessons learned. J Educ Health Promot. 2023, 12:338. 10.4103\/jehp.jehp_402_23","journal-title":"J Educ Health Promot"},{"key":"ref122","doi-asserted-by":"publisher","DOI":"10.1177\/0706743719828977","article-title":"Chatbots and conversational agents in mental health: a review of the psychiatric landscape","volume":"64","author":"Vaidyam AN","year":"2019","unstructured":"Vaidyam AN, Wisniewski H, Halamka JD, Kashavan MS, Torous JB. Chatbots and conversational agents in mental health: a review of the psychiatric landscape. Can J Psychiatry. 2019, 64:456-64. 10.1177\/0706743719828977","journal-title":"Can J Psychiatry"},{"key":"ref123","doi-asserted-by":"publisher","DOI":"10.2196\/42301","article-title":"Leveraging mobile health to manage mental health\/behavioral health disorders: systematic literature review","volume":"9","author":"Kruse CS","year":"2022","unstructured":"Kruse CS, Betancourt JA, Gonzales M, Dickerson K, Neer M. Leveraging mobile health to manage mental health\/behavioral health disorders: systematic literature review. JMIR Ment Health. 2022, 9:e42301. 10.2196\/42301","journal-title":"JMIR Ment Health"},{"key":"ref124","doi-asserted-by":"publisher","DOI":"10.1186\/s12888-023-05114-y","article-title":"Digital tools to support mental health: a survey study in psychosis","volume":"23","author":"Eisner E","year":"2023","unstructured":"Eisner E, Berry N, Bucci S. Digital tools to support mental health: a survey study in psychosis. BMC Psychiatry. 2023, 23:726. 10.1186\/s12888-023-05114-y","journal-title":"BMC Psychiatry"},{"key":"ref125","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2020.04.026","article-title":"Artificial intelligence and neuropsychological measures: the case of Alzheimer's disease","volume":"114","author":"Battista P","year":"2020","unstructured":"Battista P, Salvatore C, Berlingeri M, Cerasa A, Castiglioni I. Artificial intelligence and neuropsychological measures: the case of Alzheimer's disease. Neurosci Biobehav Rev. 2020, 114:211-28. 10.1016\/j.neubiorev.2020.04.026","journal-title":"Neurosci Biobehav Rev"}],"container-title":["Cureus"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cureus.com\/articles\/233758-the-role-of-artificial-intelligence-in-identifying-depression-and-anxiety-a-comprehensive-literature-review","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,19]],"date-time":"2024-03-19T16:51:05Z","timestamp":1710867065000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cureus.com\/articles\/233758-the-role-of-artificial-intelligence-in-identifying-depression-and-anxiety-a-comprehensive-literature-review"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,19]]},"references-count":125,"URL":"https:\/\/doi.org\/10.7759\/cureus.56472","relation":{},"ISSN":["2168-8184"],"issn-type":[{"value":"2168-8184","type":"print"}],"subject":[],"published":{"date-parts":[[2024,3,19]]}}}