{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T07:34:49Z","timestamp":1771572889333,"version":"3.50.1"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T00:00:00Z","timestamp":1690761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T00:00:00Z","timestamp":1690761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["MOST110-2314-B-016-010-MY3"],"award-info":[{"award-number":["MOST110-2314-B-016-010-MY3"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["MOST111-2321-B-016-003"],"award-info":[{"award-number":["MOST111-2321-B-016-003"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005937","name":"Cheng Hsin General Hospital Foundation","doi-asserted-by":"publisher","award":["CHNDMC-111-07"],"award-info":[{"award-number":["CHNDMC-111-07"]}],"id":[{"id":"10.13039\/501100005937","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019000","name":"Medical Affairs Bureau","doi-asserted-by":"publisher","award":["MND-MAB-110-113"],"award-info":[{"award-number":["MND-MAB-110-113"]}],"id":[{"id":"10.13039\/501100019000","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019000","name":"Medical Affairs Bureau","doi-asserted-by":"publisher","award":["MND-MAB-C13-112053"],"award-info":[{"award-number":["MND-MAB-C13-112053"]}],"id":[{"id":"10.13039\/501100019000","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Tri-Serive General Hospital, Taiwan","award":["TSGH-E-112215"],"award-info":[{"award-number":["TSGH-E-112215"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Med Syst"],"DOI":"10.1007\/s10916-023-01980-x","type":"journal-article","created":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T09:01:56Z","timestamp":1690794116000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["An AI-Enabled Dynamic Risk Stratification for Emergency Department Patients with ECG and CXR Integration"],"prefix":"10.1007","volume":"47","author":[{"given":"Yu-Hsuan Jamie","family":"Chen","sequence":"first","affiliation":[]},{"given":"Chin-Sheng","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Chin","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Dung-Jang","family":"Tsai","sequence":"additional","affiliation":[]},{"given":"Wen-Hui","family":"Fang","sequence":"additional","affiliation":[]},{"given":"Chia-Cheng","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Chih-Hung","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Sy-Jou","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,7,31]]},"reference":[{"key":"1980_CR1","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1186\/1757-7241-19-42","volume":"19","author":"N Farrohknia","year":"2011","unstructured":"N. Farrohknia, M. Castren, A. Ehrenberg, L. Lind, S. Oredsson, H. Jonsson, K. Asplund, K.E. Goransson, Emergency department triage scales and their components: a systematic review of the scientific evidence, Scand J Trauma Resusc Emerg Med 19 (2011) 42.","journal-title":"Scand J Trauma Resusc Emerg Med"},{"key":"1980_CR2","doi-asserted-by":"crossref","unstructured":"C.M. Fernandes, P. Tanabe, N. Gilboy, L.A. Johnson, R.S. McNair, A.M. Rosenau, P. Sawchuk, D.A. Thompson, D.A. Travers, N. Bonalumi, R.E. Suter, Five-level triage: a report from the ACEP\/ENA Five-level Triage Task Force, J Emerg Nurs 31(1) (2005) 39-50; quiz 118.","DOI":"10.1016\/j.jen.2004.11.002"},{"issue":"17","key":"1980_CR3","doi-asserted-by":"publisher","first-page":"2151","DOI":"10.1001\/jama.288.17.2151","volume":"288","author":"PJ Pronovost","year":"2002","unstructured":"P.J. Pronovost, D.C. Angus, T. Dorman, K.A. Robinson, T.T. Dremsizov, T.L. Young, Physician staffing patterns and clinical outcomes in critically ill patients: a systematic review, Jama 288(17) (2002) 2151-2162.","journal-title":"Jama"},{"issue":"3","key":"1980_CR4","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1136\/emermed-2021-211572","volume":"39","author":"S Jones","year":"2022","unstructured":"S. Jones, C. Moulton, S. Swift, P. Molyneux, S. Black, N. Mason, R. Oakley, C. Mann, Association between delays to patient admission from the emergency department and all-cause 30-day mortality, Emergency medicine journal : EMJ 39(3) (2022) 168-173.","journal-title":"Emergency medicine journal : EMJ"},{"key":"1980_CR5","unstructured":"N. Gilboy, T. Tanabe, D. Travers, A.M. Rosenau, Emergency Severity Index (ESI): A Triage Tool for Emergency Department Care, 4th ed., Emergency Nurses Association2020."},{"key":"1980_CR6","doi-asserted-by":"crossref","unstructured":"F.A. Nishi, F. de Oliveira Motta Maia, I. de Souza Santos, D. de Almeida Lopes Monteiro da Cruz, Assessing sensitivity and specificity of the Manchester Triage System in the evaluation of acute coronary syndrome in adult patients in emergency care: a systematic review, JBI Database System Rev Implement Rep 15(6) (2017) 1747-1761.","DOI":"10.11124\/JBISRIR-2016-003139"},{"issue":"2","key":"1980_CR7","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/S0196-0644(99)70223-4","volume":"34","author":"R Beveridge","year":"1999","unstructured":"R. Beveridge, J. Ducharme, L. Janes, S. Beaulieu, S. Walter, Reliability of the Canadian emergency department triage and acuity scale: interrater agreement, Ann Emerg Med 34(2) (1999) 155-9.","journal-title":"Ann Emerg Med"},{"key":"1980_CR8","doi-asserted-by":"crossref","unstructured":"C.J. Ng, Z.S. Yen, J.C. Tsai, L.C. Chen, S.J. Lin, Y.Y. Sang, J.C. Chen, T.n.w. group, Validation of the Taiwan triage and acuity scale: a new computerised five-level triage system, Emerg Med J 28(12) (2011) 1026-31.","DOI":"10.1136\/emj.2010.094185"},{"issue":"1","key":"1980_CR9","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.annemergmed.2018.09.022","volume":"74","author":"JS Hinson","year":"2019","unstructured":"J.S. Hinson, D.A. Martinez, S. Cabral, K. George, M. Whalen, B. Hansoti, S. Levin, Triage Performance in Emergency Medicine: A Systematic Review, Annals of emergency medicine 74(1) (2019) 140-152.","journal-title":"Annals of emergency medicine"},{"key":"1980_CR10","doi-asserted-by":"crossref","unstructured":"T. Htay, K. Aung, Review: Some ED triage systems better predict ED mortality than in-hospital mortality or hospitalization, Ann Intern Med 170(8) (2019) JC47.","DOI":"10.7326\/ACPJ201904160-047"},{"issue":"5","key":"1980_CR11","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1111\/j.1365-2796.2004.01321.x","volume":"255","author":"T Olsson","year":"2004","unstructured":"T. Olsson, A. Terent, L. Lind, Rapid Emergency Medicine score: a new prognostic tool for in-hospital mortality in nonsurgical emergency department patients, J Intern Med 255(5) (2004) 579-87.","journal-title":"J Intern Med"},{"issue":"2","key":"1980_CR12","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/j.ajem.2019.02.004","volume":"38","author":"SB Lee","year":"2020","unstructured":"S.B. Lee, D.H. Kim, T. Kim, C. Kang, S.H. Lee, J.H. Jeong, S.C. Kim, Y.J. Park, D. Lim, Emergency Department Triage Early Warning Score (TREWS) predicts in-hospital mortality in the emergency department, Am J Emerg Med 38(2) (2020) 203-210.","journal-title":"Am J Emerg Med"},{"key":"1980_CR13","unstructured":"T.C. Lu, C.H. Wang, F.Y. Chou, J.T. Sun, E.H. Chou, E.P. Huang, C.L. Tsai, M.H. Ma, C.C. Fang, C.H. Huang, Machine learning to predict in-hospital cardiac arrest from patients presenting to the emergency department, Intern Emerg Med (2022)."},{"issue":"8","key":"1980_CR14","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2021.18467","volume":"4","author":"F Xie","year":"2021","unstructured":"F. Xie, M.E.H. Ong, J. Liew, K.B.K. Tan, A.F.W. Ho, G.D. Nadarajan, L.L. Low, Y.H. Kwan, B.A. Goldstein, D.B. Matchar, B. Chakraborty, N. Liu, Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions, JAMA Netw Open 4(8) (2021) e2118467.","journal-title":"JAMA Netw Open"},{"key":"1980_CR15","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1038\/s41746-020-00324-0","volume":"3","author":"S Benjamens","year":"2020","unstructured":"S. Benjamens, P. Dhunnoo, B. Mesk\u00f3, The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database, NPJ Digit Med 3 (2020) 118.","journal-title":"NPJ Digit Med"},{"key":"1980_CR16","doi-asserted-by":"crossref","unstructured":"S. Raghunath, A.E. Ulloa Cerna, L. Jing, D.P. vanMaanen, J. Stough, D.N. Hartzel, J.B. Leader, H.L. Kirchner, M.C. Stumpe, A. Hafez, A. Nemani, T. Carbonati, K.W. Johnson, K. Young, C.W. Good, J.M. Pfeifer, A.A. Patel, B.P. Delisle, A. Alsaid, D. Beer, C.M. Haggerty, B.K. Fornwalt, Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network, Nature medicine 26(6) (2020) 886-891.","DOI":"10.1038\/s41591-020-0870-z"},{"issue":"7","key":"1980_CR17","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2019.7416","volume":"2","author":"MT Lu","year":"2019","unstructured":"M.T. Lu, A. Ivanov, T. Mayrhofer, A. Hosny, H. Aerts, U. Hoffmann, Deep Learning to Assess Long-term Mortality From Chest Radiographs, JAMA network open 2(7) (2019) e197416.","journal-title":"JAMA network open"},{"issue":"2","key":"1980_CR18","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1378\/chest.126.2.461","volume":"126","author":"D Brieger","year":"2004","unstructured":"D. Brieger, K.A. Eagle, S.G. Goodman, P.G. Steg, A. Budaj, K. White, G. Montalescot, Acute coronary syndromes without chest pain, an underdiagnosed and undertreated high-risk group: insights from the Global Registry of Acute Coronary Events, Chest 126(2) (2004) 461-9.","journal-title":"Chest"},{"issue":"12","key":"1980_CR19","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0243373","volume":"15","author":"PF Huang","year":"2020","unstructured":"P.F. Huang, P.T. Kung, W.Y. Chou, W.C. Tsai, Characteristics and related factors of emergency department visits, readmission, and hospital transfers of inpatients under a DRG-based payment system: a nationwide cohort study, PloS one 15(12) (2020) e0243373.","journal-title":"PloS one"},{"issue":"8","key":"1980_CR20","doi-asserted-by":"publisher","first-page":"725","DOI":"10.3390\/jpm11080725","volume":"11","author":"CS Lin","year":"2021","unstructured":"C.S. Lin, Y.T. Lee, W.H. Fang, Y.S. Lou, F.C. Kuo, C.C. Lee, C. Lin, Deep learning algorithm for management of diabetes mellitus via electrocardiogram-based glycated hemoglobin (ECG-HbA1c): a retrospective cohort study, J Pers Med 11(8) (2021) 725.","journal-title":"J Pers Med"},{"issue":"2","key":"1980_CR21","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1016\/j.cjca.2021.09.028","volume":"38","author":"WT Liu","year":"2022","unstructured":"W.T. Liu, C.S. Lin, T.P. Tsao, C.C. Lee, C.C. Cheng, J.T. Chen, C.S. Tsai, W.S. Lin, C. Lin, A deep-learning algorithm-enhanced system integrating electrocardiograms and chest X-rays for diagnosing aortic dissection, The Canadian journal of cardiology 38(2) (2022) 160-168.","journal-title":"The Canadian journal of cardiology"},{"issue":"6","key":"1980_CR22","doi-asserted-by":"publisher","first-page":"1691","DOI":"10.1002\/emp2.12277","volume":"1","author":"A Kirubarajan","year":"2020","unstructured":"A. Kirubarajan, A. Taher, S. Khan, S. Masood, Artificial intelligence in emergency medicine: A scoping review, Journal of the American College of Emergency Physicians open 1(6) (2020) 1691-1702.","journal-title":"Journal of the American College of Emergency Physicians open"},{"key":"1980_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.ibmed.2021.100039","volume":"5","author":"C Mosquera","year":"2021","unstructured":"C. Mosquera, F. Binder, F.N. Diaz, A. Seehaus, G. Ducrey, J.A. Ocantos, M. Aineseder, L. Rubin, D.A. Rabinovich, A.E. Quiroga, Integration of a deep learning system for automated chest x-ray interpretation in the emergency department: A proof-of-concept, Intelligence-Based Medicine 5 (2021) 100039.","journal-title":"Intelligence-Based Medicine"},{"issue":"7","key":"1980_CR24","doi-asserted-by":"publisher","first-page":"1150","DOI":"10.3390\/jpm12071150","volume":"12","author":"YL Liu","year":"2022","unstructured":"Y.L. Liu, C.S. Lin, C.C. Cheng, C. Lin, A deep learning algorithm for detecting acute pericarditis by electrocardiogram, J Pers Med 12(7) (2022) 1150.","journal-title":"J Pers Med"},{"issue":"4","key":"1980_CR25","doi-asserted-by":"publisher","first-page":"3317","DOI":"10.1007\/s00068-022-01904-3","volume":"48","author":"CC Lee","year":"2022","unstructured":"C.C. Lee, C.S. Lin, C.S. Tsai, T.P. Tsao, C.C. Cheng, J.T. Liou, W.S. Lin, C.C. Lee, J.T. Chen, C. Lin, A deep learning-based system capable of detecting pneumothorax via electrocardiogram, European journal of trauma and emergency surgery : official publication of the European Trauma Society 48(4) (2022) 3317-3326.","journal-title":"European journal of trauma and emergency surgery : official publication of the European Trauma Society"},{"issue":"9","key":"1980_CR26","first-page":"765","volume":"17","author":"WC Liu","year":"2021","unstructured":"W.C. Liu, C.S. Lin, C.S. Tsai, T.P. Tsao, C.C. Cheng, J.T. Liou, W.S. Lin, S.M. Cheng, Y.S. Lou, C.C. Lee, C. Lin, A deep-learning algorithm for detecting acute myocardial infarction, EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology 17(9) (2021) 765-773.","journal-title":"Cardiology"},{"issue":"7","key":"1980_CR27","doi-asserted-by":"publisher","first-page":"3839","DOI":"10.3390\/ijerph18073839","volume":"18","author":"DW Chang","year":"2021","unstructured":"D.W. Chang, C.S. Lin, T.P. Tsao, C.C. Lee, J.T. Chen, C.S. Tsai, W.S. Lin, C. Lin, Detecting digoxin toxicity by artificial intelligence-assisted electrocardiography, International journal of environmental research and public health 18(7) (2021) 3839.","journal-title":"International journal of environmental research and public health"},{"issue":"3","key":"1980_CR28","doi-asserted-by":"publisher","DOI":"10.2196\/15931","volume":"8","author":"CS Lin","year":"2020","unstructured":"C.S. Lin, C. Lin, W.H. Fang, C.J. Hsu, S.J. Chen, K.H. Huang, W.S. Lin, C.S. Tsai, C.C. Kuo, T. Chau, S.J. Yang, S.H. Lin, A deep-learning algorithm (ECG12Net) for detecting hypokalemia and hyperkalemia by electrocardiography: algorithm development, JMIR medical informatics 8(3) (2020) e15931.","journal-title":"JMIR medical informatics"},{"key":"1980_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2019.101762","volume":"102","author":"M Fernandes","year":"2020","unstructured":"M. Fernandes, S.M. Vieira, F. Leite, C. Palos, S. Finkelstein, J.M.C. Sousa, Clinical Decision Support Systems for Triage in the Emergency Department using Intelligent Systems: a Review, Artif Intell Med 102 (2020) 101762.","journal-title":"Artif Intell Med"},{"issue":"1","key":"1980_CR30","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1186\/s13054-019-2351-7","volume":"23","author":"Y Raita","year":"2019","unstructured":"Y. Raita, T. Goto, M.K. Faridi, D.F.M. Brown, C.A. Camargo, Jr., K. Hasegawa, Emergency department triage prediction of clinical outcomes using machine learning models, Crit Care 23(1) (2019) 64.","journal-title":"Crit Care"},{"issue":"12","key":"1980_CR31","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1001\/jama.2019.1696","volume":"321","author":"LW Andersen","year":"2019","unstructured":"L.W. Andersen, M.J. Holmberg, K.M. Berg, M.W. Donnino, A. Granfeldt, In-Hospital Cardiac Arrest: A Review, JAMA 321(12) (2019) 1200-1210.","journal-title":"JAMA"},{"issue":"2","key":"1980_CR32","doi-asserted-by":"publisher","first-page":"315","DOI":"10.3390\/jpm12020315","volume":"12","author":"YS Lou","year":"2022","unstructured":"Y.S. Lou, C.S. Lin, W.H. Fang, C.C. Lee, C.L. Ho, C.H. Wang, C. Lin, Artificial intelligence-enabled electrocardiogram estimates left atrium enlargement as a predictor of future cardiovascular disease, J Pers Med 12(2) (2022) 315.","journal-title":"J Pers Med"},{"issue":"1","key":"1980_CR33","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1038\/s41746-021-00550-0","volume":"5","author":"C Lin","year":"2022","unstructured":"C. Lin, T. Chau, C.S. Lin, H.S. Shang, W.H. Fang, D.J. Lee, C.C. Lee, S.H. Tsai, C.H. Wang, S.H. Lin, Point-of-care artificial intelligence-enabled ECG for dyskalemia: a retrospective cohort analysis for accuracy and outcome prediction, NPJ Digit Med 5(1) (2022) 8.","journal-title":"NPJ Digit Med"},{"key":"1980_CR34","doi-asserted-by":"publisher","DOI":"10.3389\/fcvm.2022.895201","volume":"9","author":"YT Lee","year":"2022","unstructured":"Y.T. Lee, C.S. Lin, W.H. Fang, C.C. Lee, C.L. Ho, C.H. Wang, D.J. Tsai, C. Lin, Artificial Intelligence-Enabled Electrocardiography Detects Hypoalbuminemia and Identifies the Mechanism of Hepatorenal and Cardiovascular Events, Frontiers in cardiovascular medicine 9 (2022) 895201.","journal-title":"Frontiers in cardiovascular medicine"},{"issue":"12","key":"1980_CR35","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1097\/00005650-200212000-00004","volume":"40","author":"PA Glassman","year":"2002","unstructured":"P.A. Glassman, B. Simon, P. Belperio, A. Lanto, Improving recognition of drug interactions: benefits and barriers to using automated drug alerts, Medical care 40(12) (2002) 1161-71.","journal-title":"Medical care"},{"issue":"7","key":"1980_CR36","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1038\/s41569-020-00503-2","volume":"18","author":"KC Siontis","year":"2021","unstructured":"K.C. Siontis, P.A. Noseworthy, Z.I. Attia, P.A. Friedman, Artificial intelligence-enhanced electrocardiography in cardiovascular disease management, Nature reviews. Cardiology 18(7) (2021) 465-478.","journal-title":"Nature reviews. Cardiology"},{"key":"1980_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102125","volume":"72","author":"E \u00c7all\u0131","year":"2021","unstructured":"E. \u00c7all\u0131, E. Sogancioglu, B. van Ginneken, K.G. van Leeuwen, K. Murphy, Deep learning for chest X-ray analysis: A survey, Medical image analysis 72 (2021) 102125.","journal-title":"Medical image analysis"},{"issue":"3","key":"1980_CR38","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1001\/archinternmed.2008.551","volume":"169","author":"T Isaac","year":"2009","unstructured":"T. Isaac, J.S. Weissman, R.B. Davis, M. Massagli, A. Cyrulik, D.Z. Sands, S.N. Weingart, Overrides of medication alerts in ambulatory care, Archives of internal medicine 169(3) (2009) 305-11.","journal-title":"Archives of internal medicine"},{"key":"1980_CR39","doi-asserted-by":"crossref","unstructured":"D.J. Tsai, S.H. Tsai, H.H. Chiang, C.C. Lee, S.J. Chen, Development and Validation of an Artificial Intelligence Electrocardiogram Recommendation System in the Emergency Department, J Pers Med 12(5) (2022).","DOI":"10.3390\/jpm12050700"}],"container-title":["Journal of Medical Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-023-01980-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10916-023-01980-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-023-01980-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T06:15:49Z","timestamp":1703830549000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10916-023-01980-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,31]]},"references-count":39,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["1980"],"URL":"https:\/\/doi.org\/10.1007\/s10916-023-01980-x","relation":{},"ISSN":["1573-689X"],"issn-type":[{"value":"1573-689X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,31]]},"assertion":[{"value":"12 April 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 July 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The Tri-Service General Hospital, Taipei, Taiwan, conducted the ethical review of this study (IRB No. C202105049). The institutional review board agreed to waive individual consent since the data were collected retrospectively and analyzed on the intranet.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"81"}}