{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T15:07:53Z","timestamp":1780585673970,"version":"3.54.1"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,4]]},"DOI":"10.7759\/cureus.110241","type":"journal-article","created":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T14:39:01Z","timestamp":1780583941000},"source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence for Neonatal Sepsis Prediction: A Review of Advances, Clinical Integration, and Future Prospects"],"prefix":"10.7759","author":[{"given":"Joyce O","family":"Ndubuisi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Igboanude","family":"Chimaoge Henry","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oranu  G","family":"Ibekie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Winifred","family":"Oniah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gandu T","family":"Purity","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Johnbosco  C","family":"Nnamani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oiku  M","family":"Omofuma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ubochioma  D","family":"Chimdike","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nwachi","family":"Divine","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Izuchukwu Jonathan","family":"Obidiegwu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Umeozulu","family":"Jessica Ifunanya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Prestige","family":"Okonkwo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Osinigwe","family":"Ibekie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nwachukwu","family":"Chinenye Benita","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick","family":"Ashinze","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2023.1156732","article-title":"Sepsis and infection: two words that should not be confused","volume":"10","author":"Vincent JL","year":"2023","unstructured":"Vincent JL. Sepsis and infection: two words that should not be confused. Front Med (Lausanne). 2023, 10:1156732. 10.3389\/fmed.2023.1156732","journal-title":"Front Med (Lausanne)"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1097\/MOP.0000000000000315","article-title":"Defining neonatal sepsis","volume":"28","author":"Wynn JL","year":"2016","unstructured":"Wynn JL. Defining neonatal sepsis. Curr Opin Pediatr. 2016, 28:135-40. 10.1097\/MOP.0000000000000315","journal-title":"Curr Opin Pediatr"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s00590-016-1776-9","article-title":"Neonatal septic arthritis in a tertiary care hospital: a descriptive study","volume":"26","author":"Sreenivas T","year":"2016","unstructured":"Sreenivas T, Nataraj AR, Kumar A, Menon J. Neonatal septic arthritis in a tertiary care hospital: a descriptive study. Eur J Orthop Surg Traumatol. 2016, 26:477-81. 10.1007\/s00590-016-1776-9","journal-title":"Eur J Orthop Surg Traumatol"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/S1473-3099(14)70804-7","article-title":"Estimates of possible severe bacterial infection in neonates in sub-Saharan Africa, south Asia, and Latin America for 2012: a systematic review and meta-analysis","volume":"14","author":"Seale AC","year":"2014","unstructured":"Seale AC, Blencowe H, Manu AA, et al.. Estimates of possible severe bacterial infection in neonates in sub-Saharan Africa, south Asia, and Latin America for 2012: a systematic review and meta-analysis. Lancet Infect Dis. 2014, 14:731-41. 10.1016\/S1473-3099(14)70804-7","journal-title":"Lancet Infect Dis"},{"key":"ref5","article-title":"Global Report on the Epidemiology and Burden of Sepsis: Current Evidence, Identifying Gaps and Future Directions","author":"World Health Organization","year":"2020","unstructured":"World Health Organization. Global Report on the Epidemiology and Burden of Sepsis: Current Evidence, Identifying Gaps and Future Directions. WHO, Geneva; 2020."},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/S2214-109X(22)00043-2","article-title":"Neonatal sepsis and mortality in low-income and middle-income countries from a facility-based birth cohort: an international multisite prospective observational study","volume":"10","author":"Milton R","year":"2022","unstructured":"Milton R, Gillespie D, Dyer C, et al.. Neonatal sepsis and mortality in low-income and middle-income countries from a facility-based birth cohort: an international multisite prospective observational study. Lancet Glob Health. 2022, 10:e661-72. 10.1016\/S2214-109X(22)00043-2","journal-title":"Lancet Glob Health"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1186\/s12884-024-06583-z","article-title":"Magnitude of neonatal sepsis and its associated factors among neonates admitted to the neonatal intensive care unit in Hawassa Comprehensive Specialized Hospital, Sidama Regional State, Ethiopia, 2020","volume":"24","author":"Baheru FS","year":"2024","unstructured":"Baheru FS, Shiferaw BZ, Toru T, GebreEyesus FA. Magnitude of neonatal sepsis and its associated factors among neonates admitted to the neonatal intensive care unit in Hawassa Comprehensive Specialized Hospital, Sidama Regional State, Ethiopia, 2020. BMC Pregnancy Childbirth. 2024, 24:383. 10.1186\/s12884-024-06583-z","journal-title":"BMC Pregnancy Childbirth"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1097\/INF.0b013e318223bad2","article-title":"The burden of invasive early-onset neonatal sepsis in the United States, 2005-2008","volume":"30","author":"Weston EJ","year":"2011","unstructured":"Weston EJ, Pondo T, Lewis MM, et al.. The burden of invasive early-onset neonatal sepsis in the United States, 2005-2008. Pediatr Infect Dis J. 2011, 30:937-41. 10.1097\/INF.0b013e318223bad2","journal-title":"Pediatr Infect Dis J"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.2471\/BLT.14.139790","article-title":"Neonatal cause-of-death estimates for the early and late neonatal periods for 194 countries: 2000-2013","volume":"93","author":"Oza S","year":"2015","unstructured":"Oza S, Lawn JE, Hogan DR, Mathers C, Cousens SN. Neonatal cause-of-death estimates for the early and late neonatal periods for 194 countries: 2000-2013. Bull World Health Organ. 2015, 93:19-28. 10.2471\/BLT.14.139790","journal-title":"Bull World Health Organ"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.pcl.2012.12.003","article-title":"Neonatal infectious diseases: evaluation of neonatal sepsis","volume":"60","author":"Camacho-Gonzalez A","year":"2013","unstructured":"Camacho-Gonzalez A, Spearman PW, Stoll BJ. Neonatal infectious diseases: evaluation of neonatal sepsis. Pediatr Clin North Am. 2013, 60:367-89. 10.1016\/j.pcl.2012.12.003","journal-title":"Pediatr Clin North Am"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1128\/JCM.00140-07","article-title":"Is the volume of blood cultured still a significant factor in the diagnosis of bloodstream infections?","volume":"45","author":"Bouza E","year":"2007","unstructured":"Bouza E, Sousa D, Rodr\u00edguez-Cr\u00e9ixems M, Lechuz JG, Mu\u00f1oz P. Is the volume of blood cultured still a significant factor in the diagnosis of bloodstream infections?. J Clin Microbiol. 2007, 45:2765-9. 10.1128\/JCM.00140-07","journal-title":"J Clin Microbiol"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1097\/INF.0b013e3181958755","article-title":"Burden of neonatal infections in developing countries: a review of evidence from community-based studies","volume":"28","author":"Thaver D","year":"2009","unstructured":"Thaver D, Zaidi AK. Burden of neonatal infections in developing countries: a review of evidence from community-based studies. Pediatr Infect Dis J. 2009, 28:S3-9. 10.1097\/INF.0b013e3181958755","journal-title":"Pediatr Infect Dis J"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/BF01708346","article-title":"Comparison of five days versus seven days of incubation for detection of positive blood cultures by the Bactec 9240 system","volume":"17","author":"Huang AH","year":"1998","unstructured":"Huang AH, Yan JJ, Wu JJ. Comparison of five days versus seven days of incubation for detection of positive blood cultures by the Bactec 9240 system. Eur J Clin Microbiol Infect Dis. 1998, 17:637-41. 10.1007\/BF01708346","journal-title":"Eur J Clin Microbiol Infect Dis"},{"key":"ref14","article-title":"Antibiotics for Early-Onset Neonatal Infection: Clinical Guideline CG149. NICE, London, 2012","author":"National Institute for Health and Care Excellence","year":"2014","unstructured":"National Institute for Health and Care Excellence. Antibiotics for Early-Onset Neonatal Infection: Clinical Guideline CG149. NICE, London, 2012. National Institute for Health and Care Excellence (NICE), London; 2014."},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3389\/fped.2018.00285","article-title":"Culture-negative early-onset neonatal sepsis - at the crossroad between efficient sepsis care and antimicrobial stewardship","volume":"6","author":"Klingenberg C","year":"2018","unstructured":"Klingenberg C, Kornelisse RF, Buonocore G, Maier RF, Stocker M. Culture-negative early-onset neonatal sepsis - at the crossroad between efficient sepsis care and antimicrobial stewardship. Front Pediatr. 2018, 6:285. 10.3389\/fped.2018.00285","journal-title":"Front Pediatr"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1097\/INF.0000000000000906","article-title":"Early-onset sepsis and antibiotic exposure in term infants: a nationwide population-based study in Norway","volume":"35","author":"Fjalstad JW","year":"2016","unstructured":"Fjalstad JW, Stensvold HJ, Bergseng H, Simonsen GS, Salvesen B, R\u00f8nnestad AE, Klingenberg C. Early-onset sepsis and antibiotic exposure in term infants: a nationwide population-based study in Norway. Pediatr Infect Dis J. 2016, 35:1-6. 10.1097\/INF.0000000000000906","journal-title":"Pediatr Infect Dis J"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/S1473-3099(16)30205-5","article-title":"Reducing unnecessary antibiotic use in the neonatal intensive care unit (SCOUT): a prospective interrupted time-series study","volume":"16","author":"Cantey JB","year":"2016","unstructured":"Cantey JB, Wozniak PS, Pruszynski JE, Sanchez PJ. Reducing unnecessary antibiotic use in the neonatal intensive care unit (SCOUT): a prospective interrupted time-series study. Lancet Infect Dis. 2016, 16:1178-84. 10.1016\/S1473-3099(16)30205-5","journal-title":"Lancet Infect Dis"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3109\/00365548.2014.971053","article-title":"Serial serum C-reactive protein levels in the diagnosis of neonatal infection","volume":"102","author":"Benitz WE","year":"1998","unstructured":"Benitz WE, Han MY, Madan A, Ramachandra P. Serial serum C-reactive protein levels in the diagnosis of neonatal infection. Pediatrics. 1998, 102:E41. 10.3109\/00365548.2014.971053","journal-title":"Pediatrics"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1001\/jamapediatrics.2019.5669","article-title":"Assessment of C-reactive protein diagnostic test accuracy for late-onset infection in newborn infants. A systematic review and meta-analysis","volume":"174","author":"Brown JV","year":"2020","unstructured":"Brown JV, Meader N, Wright K, Cleminson J, McGuire W. Assessment of C-reactive protein diagnostic test accuracy for late-onset infection in newborn infants. A systematic review and meta-analysis. JAMA Pediatr. 2020, 174:260-8. 10.1001\/jamapediatrics.2019.5669","journal-title":"JAMA Pediatr"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2431-10-89","article-title":"Neonatal Procalcitonin Intervention Study (NeoPInS): effect of procalcitonin-guided decision making on duration of antibiotic therapy in suspected neonatal early-onset sepsis: a multi-centre randomized superiority and non-inferiority intervention study","volume":"10","author":"Stocker M","year":"2010","unstructured":"Stocker M, Hop WC, van Rossum AM. Neonatal Procalcitonin Intervention Study (NeoPInS): effect of procalcitonin-guided decision making on duration of antibiotic therapy in suspected neonatal early-onset sepsis: a multi-centre randomized superiority and non-inferiority intervention study. BMC Pediatr. 2010, 10:89. 10.1186\/1471-2431-10-89","journal-title":"BMC Pediatr"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/269681","article-title":"Neonatal sepsis and inflammatory mediators","volume":"2014","author":"Machado JR","year":"2014","unstructured":"Machado JR, Soave DF, da Silva MV, et al.. Neonatal sepsis and inflammatory mediators. Mediators Inflamm. 2014, 2014:269681. 10.1155\/2014\/269681","journal-title":"Mediators Inflamm"},{"key":"ref22","article-title":"Early and late markers for the detection of early-onset neonatal sepsis","volume":"55","author":"Bender L","year":"2008","unstructured":"Bender L, Thaarup J, Varming K, Krarup H, Ellermann-Eriksen S, Ebbesen F. Early and late markers for the detection of early-onset neonatal sepsis. Dan Med Bull. 2008, 55:219-23.","journal-title":"Dan Med Bull"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.2147\/RRN.S48316","article-title":"Biomarkers for neonatal sepsis: recent developments","volume":"4","author":"Mally P","year":"2014","unstructured":"Mally P, Xu J, Hendricks-Munoz K. Biomarkers for neonatal sepsis: recent developments. Res Rep Neonatol. 2014, 4:157-68. 10.2147\/RRN.S48316","journal-title":"Res Rep Neonatol"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1042\/ETLS20210246","article-title":"Artificial intelligence, machine learning, and deep learning for clinical outcome prediction","volume":"5","author":"Pettit RW","year":"2021","unstructured":"Pettit RW, Fullem R, Cheng C, Amos CI. Artificial intelligence, machine learning, and deep learning for clinical outcome prediction. Emerg Top Life Sci. 2021, 5:729-45. 10.1042\/ETLS20210246","journal-title":"Emerg Top Life Sci"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1186\/s13054-025-05588-0","article-title":"Transforming sepsis management: AI-driven innovations in early detection and tailored therapies","volume":"29","author":"Papareddy P","year":"2025","unstructured":"Papareddy P, Lobo TJ, Holub M, Bouma H, Maca J, Strodthoff N, Herwald H. Transforming sepsis management: AI-driven innovations in early detection and tailored therapies. Crit Care. 2025, 29:366. 10.1186\/s13054-025-05588-0","journal-title":"Crit Care"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.2196\/77721","article-title":"Beyond comparing machine learning and logistic regression in clinical prediction modelling: shifting from model debate to data quality","volume":"27","author":"Hu Y","year":"2025","unstructured":"Hu Y, Zhang X, Slavin V, Belsti Y, Tiruneh SA, Callander E, Enticott J. Beyond comparing machine learning and logistic regression in clinical prediction modelling: shifting from model debate to data quality. J Med Internet Res. 2025, 27:e77721. 10.2196\/77721","journal-title":"J Med Internet Res"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2016.35","article-title":"MIMIC-III, a freely accessible critical care database","volume":"3","author":"Johnson AE","year":"2016","unstructured":"Johnson AE, Pollard TJ, Shen L, et al.. MIMIC-III, a freely accessible critical care database. Sci Data. 2016, 3:160035. 10.1038\/sdata.2016.35","journal-title":"Sci Data"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1038\/s41390-022-02274-7","article-title":"Artificial and human intelligence for early identification of neonatal sepsis","volume":"93","author":"Sullivan BA","year":"2023","unstructured":"Sullivan BA, Kausch SL, Fairchild KD. Artificial and human intelligence for early identification of neonatal sepsis. Pediatr Res. 2023, 93:350-6. 10.1038\/s41390-022-02274-7","journal-title":"Pediatr Res"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2017.18391","article-title":"Big data and machine learning in health care","volume":"319","author":"Beam AL","year":"2018","unstructured":"Beam AL, Kohane IS. Big data and machine learning in health care. JAMA. 2018, 319:1317-8. 10.1001\/jama.2017.18391","journal-title":"JAMA"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.21037\/tp-24-278","article-title":"Constructing a predictive model for early-onset sepsis in neonatal intensive care unit newborns based on SHapley Additive exPlanations explainable machine learning","volume":"13","author":"Tan X","year":"2024","unstructured":"Tan X, Zhang X, Chai J, et al.. Constructing a predictive model for early-onset sepsis in neonatal intensive care unit newborns based on SHapley Additive exPlanations explainable machine learning. Transl Pediatr. 2024, 13:1933-46. 10.21037\/tp-24-278","journal-title":"Transl Pediatr"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1177\/20552076251376968","article-title":"Maternal perinatal risk factors and full-term neonatal early-onset sepsis: a novel prediction model based on machine learning","volume":"11","author":"Youmei C","year":"2025","unstructured":"Youmei C, Min L, Xiaoqing C, Quanfu Z. Maternal perinatal risk factors and full-term neonatal early-onset sepsis: a novel prediction model based on machine learning. Digit Health. 2025, 11:20552076251376968. 10.1177\/20552076251376968","journal-title":"Digit Health"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.siny.2025.101687","article-title":"Artificial intelligence in neonatal sepsis: scope, challenges, and potential solutions!","volume":"31","author":"Kainth D","year":"2026","unstructured":"Kainth D, Agarwal R. Artificial intelligence in neonatal sepsis: scope, challenges, and potential solutions!. Semin Fetal Neonatal Med. 2026, 31:101687. 10.1016\/j.siny.2025.101687","journal-title":"Semin Fetal Neonatal Med"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2024.108335","article-title":"Continuous prediction and clinical alarm management of late-onset sepsis in preterm infants using vital signs from a patient monitor","volume":"255","author":"Yang M","year":"2024","unstructured":"Yang M, Peng Z, van Pul C, et al.. Continuous prediction and clinical alarm management of late-onset sepsis in preterm infants using vital signs from a patient monitor. Comput Methods Programs Biomed. 2024, 255:108335. 10.1016\/j.cmpb.2024.108335","journal-title":"Comput Methods Programs Biomed"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2022.3216055","article-title":"A continuous late-onset sepsis prediction algorithm for preterm infants using multimodal physiological signals from a patient monitor","volume":"27","author":"Peng Z","year":"2023","unstructured":"Peng Z, Varisco G, Long X, et al.. A continuous late-onset sepsis prediction algorithm for preterm infants using multimodal physiological signals from a patient monitor. IEEE J Biomed Health Inform. 2023, 27:550-61. 10.1109\/JBHI.2022.3216055","journal-title":"IEEE J Biomed Health Inform"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2024.105366","article-title":"Early detection of late-onset neonatal sepsis from noninvasive biosignals using deep learning: a multicenter prospective development and validation study","volume":"184","author":"Kallonen A","year":"2024","unstructured":"Kallonen A, Juutinen M, V\u00e4rri A, Carrault G, Pladys P, Beuch\u00e9e A. Early detection of late-onset neonatal sepsis from noninvasive biosignals using deep learning: a multicenter prospective development and validation study. Int J Med Inform. 2024, 184:105366. 10.1016\/j.ijmedinf.2024.105366","journal-title":"Int J Med Inform"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1542\/peds.107.1.97","article-title":"Toward the early diagnosis of neonatal sepsis and sepsis-like illness using novel heart rate analysis","volume":"107","author":"Griffin MP","year":"2001","unstructured":"Griffin MP, Moorman JR. Toward the early diagnosis of neonatal sepsis and sepsis-like illness using novel heart rate analysis. Pediatrics. 2001, 107:97-104. 10.1542\/peds.107.1.97","journal-title":"Pediatrics"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpeds.2011.06.044","article-title":"Mortality reduction by heart rate characteristic monitoring in very low birth weight neonates: a randomized trial","volume":"159","author":"Moorman JR","year":"2011","unstructured":"Moorman JR, Carlo WA, Kattwinkel J, et al.. Mortality reduction by heart rate characteristic monitoring in very low birth weight neonates: a randomized trial. J Pediatr. 2011, 159:900-6.e1. 10.1016\/j.jpeds.2011.06.044","journal-title":"J Pediatr"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.33590\/emjinnov\/19-00172","article-title":"A path for translation of machine learning products into healthcare delivery","volume":"4","author":"Sendak MP","year":"2020","unstructured":"Sendak MP, D'Arcy J, Kashyap S, et al.. A path for translation of machine learning products into healthcare delivery. EMJ Innov. 2020, 4:46-54. 10.33590\/emjinnov\/19-00172","journal-title":"EMJ Innov"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0300-7","article-title":"High-performance medicine: the convergence of human and artificial intelligence","volume":"25","author":"Topol EJ","year":"2019","unstructured":"Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019, 25:44-56. 10.1038\/s41591-018-0300-7","journal-title":"Nat Med"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1097\/00001432-200406000-00008","article-title":"Serious bacterial infections in newborn infants in developing countries","volume":"17","author":"Osrin D","year":"2004","unstructured":"Osrin D, Vergnano S, Costello A. Serious bacterial infections in newborn infants in developing countries. Curr Opin Infect Dis. 2004, 17:217-24. 10.1097\/00001432-200406000-00008","journal-title":"Curr Opin Infect Dis"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-019-0548-6","article-title":"Do no harm: a roadmap for responsible machine learning for health care","volume":"25","author":"Wiens J","year":"2019","unstructured":"Wiens J, Saria S, Sendak M, et al.. Do no harm: a roadmap for responsible machine learning for health care. Nat Med. 2019, 25:1337-40. 10.1038\/s41591-019-0548-6","journal-title":"Nat Med"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocz192","article-title":"A governance model for the application of AI in health care","volume":"27","author":"Reddy S","year":"2020","unstructured":"Reddy S, Allan S, Coghlan S, Cooper P. A governance model for the application of AI in health care. J Am Med Inform Assoc. 2020, 27:491-7. 10.1093\/jamia\/ocz192","journal-title":"J Am Med Inform Assoc"},{"key":"ref43","unstructured":"World Health Organization. Newborns. improving survival and well-being. (2020). https:\/\/www.who.int\/en\/news-room\/fact-sheets\/detail\/newborns-reducing-mortality."},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(17)31002-4","article-title":"Neonatal sepsis","volume":"390","author":"Shane AL","year":"2017","unstructured":"Shane AL, Sanchez PJ, Stoll BJ. Neonatal sepsis. Lancet. 2017, 390:1770-80. 10.1016\/S0140-6736(17)31002-4","journal-title":"Lancet"}],"container-title":["Cureus"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cureus.com\/articles\/477334-artificial-intelligence-for-neonatal-sepsis-prediction-a-review-of-advances-clinical-integration-and-future-prospects","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T14:39:03Z","timestamp":1780583943000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cureus.com\/articles\/477334-artificial-intelligence-for-neonatal-sepsis-prediction-a-review-of-advances-clinical-integration-and-future-prospects"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,4]]},"references-count":44,"URL":"https:\/\/doi.org\/10.7759\/cureus.110241","relation":{},"ISSN":["2168-8184"],"issn-type":[{"value":"2168-8184","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6,4]]}}}