{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:23:06Z","timestamp":1772119386072,"version":"3.50.1"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"18","license":[{"start":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T00:00:00Z","timestamp":1609804800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T00:00:00Z","timestamp":1609804800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1007\/s00521-020-05592-1","type":"journal-article","created":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T06:14:51Z","timestamp":1609827291000},"page":"13037-13046","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Development and external evaluation of predictions models for mortality of COVID-19 patients using machine learning method"],"prefix":"10.1007","volume":"35","author":[{"given":"Simin","family":"Li","sequence":"first","affiliation":[]},{"given":"Yulan","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Tong","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Mengjie","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Shicheng","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Weihao","family":"Qiu","sequence":"additional","affiliation":[]},{"given":"Can","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Linfeng","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yao","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jun","family":"Yan","sequence":"additional","affiliation":[]},{"given":"Justin","family":"Wong","sequence":"additional","affiliation":[]},{"given":"Lin","family":"Naing","sequence":"additional","affiliation":[]},{"given":"Shabei","family":"Xu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,1,5]]},"reference":[{"key":"5592_CR1","doi-asserted-by":"publisher","first-page":"100124","DOI":"10.1016\/j.onehlt.2020.100124","volume":"9","author":"ME El Zowalaty","year":"2020","unstructured":"El Zowalaty ME, J\u00e4rhult JD (2020) From SARS to COVID-19: A previously unknown SARS- related coronavirus (SARS-CoV-2) of pandemic potential infecting humans-call for a one health approach. One Health (Amst, Neth) 9:100124","journal-title":"One Health (Amst, Neth)"},{"key":"5592_CR2","unstructured":"WHO Coronavirus disease situation reports, 16 April 2020. https:\/\/www.who.int\/emergencies\/diseases\/novel-coronavirus-2019\/situation-reports"},{"issue":"11","key":"5592_CR3","doi-asserted-by":"publisher","first-page":"2511","DOI":"10.1002\/jmv.25891","volume":"92","author":"F Yang","year":"2020","unstructured":"Yang F, Shi S, Zhu J, Shi J, Dai K, Chen X (2020) Analysis of 92 deceased patients with COVID-19. J Med Virol 92(11):2511\u20132515. https:\/\/doi.org\/10.1002\/jmv.25891","journal-title":"J Med Virol"},{"key":"5592_CR4","doi-asserted-by":"publisher","first-page":"343","DOI":"10.15585\/mmwr.mm6912e2","volume":"69","author":"CDC COVID-19 Response Team","year":"2020","unstructured":"CDC COVID-19 Response Team (2020) Severe Outcomes Among Patients with Coronavirus Disease 2019 (COVID-19)\u2014United States, February 12\u2013March 16, 2020. MMWR Morb Mortal Wkly Rep 69:343\u2013346. https:\/\/doi.org\/10.15585\/mmwr.mm6912e2","journal-title":"MMWR Morb Mortal Wkly Rep"},{"key":"5592_CR5","doi-asserted-by":"publisher","unstructured":"Tyrrell CSB, Mytton OT, Gentry SV, Thomas-Meyer M, Allen JLY, Narula AA, McGrath B, Lupton M, Broadbent J, Ahmed A, Mavrodaris A, Abdul Pari AA (2020) Managing intensive care admissions when there are not enough beds during the COVID-19 pandemic: a systematic review. Thorax. https:\/\/doi.org\/10.1136\/thoraxjnl-2020-215518","DOI":"10.1136\/thoraxjnl-2020-215518"},{"key":"5592_CR6","doi-asserted-by":"publisher","first-page":"m1328","DOI":"10.1136\/bmj.m1328","volume":"369","author":"L Wynants","year":"2020","unstructured":"Wynants L, Van Calster B, Bonten MMJ et al (2020) Prediction models for diagnosis and prognosis of covid-19 infection: systematic review and critical appraisal. BMJ 369:m1328","journal-title":"BMJ"},{"issue":"6","key":"5592_CR7","doi-asserted-by":"publisher","first-page":"1393","DOI":"10.1093\/cid\/ciaa414","volume":"71","author":"D Ji","year":"2020","unstructured":"Ji D, Zhang D, Xu J, Chen Z, Yang T, Zhao P, Chen G, Cheng G, Wang Y, Bi J, Tan L, Lau G, Qin E (2020) Prediction for progression risk in patients with COVID-19 pneumonia: the CALL score. Clin Infect Dis 71(6):1393\u20131399. https:\/\/doi.org\/10.1093\/cid\/ciaa414","journal-title":"Clin Infect Dis"},{"key":"5592_CR8","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1038\/s41392-020-0148-4","volume":"5","author":"L Tan","year":"2020","unstructured":"Tan L, Wang Q, Zhang D et al (2020) Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study. Signal Transduct Target Ther 5:33","journal-title":"Signal Transduct Target Ther"},{"issue":"1","key":"5592_CR9","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1186\/s13054-020-2833-7","volume":"24","author":"Y Shi","year":"2020","unstructured":"Shi Y, Yu X, Zhao H, Wang H, Zhao R, Sheng J (2020) Host susceptibility to severe COVID-19 and establishment of a host risk score: findings of 487 cases outside Wuhan. Crit Care (Lond, Engl 24(1):108","journal-title":"Crit Care (Lond, Engl"},{"issue":"3","key":"5592_CR10","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1111\/liv.14380","volume":"40","author":"A M\u00e4hringer-Kunz","year":"2020","unstructured":"M\u00e4hringer-Kunz A, Wagner F, Hahn F et al (2020) Predicting survival after transarterial chemoembolization for hepatocellular carcinoma using a neural network: a pilot study. Liver Int: Off J Int Assoc Study Liver 40(3):694\u2013703","journal-title":"Liver Int : Off J Int Assoc Study Liver"},{"key":"5592_CR11","doi-asserted-by":"publisher","first-page":"8068913","DOI":"10.1155\/2020\/8068913","volume":"2020","author":"C Cui","year":"2020","unstructured":"Cui C, Wang S, Zhou J et al (2020) Machine learning analysis of image data based on detailed MR image reports for nasopharyngeal carcinoma prognosis. Biomed Res Int 2020:8068913","journal-title":"Biomed Res Int"},{"key":"5592_CR12","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.canlet.2020.03.032","volume":"481","author":"R Cuocolo","year":"2020","unstructured":"Cuocolo R, Caruso M, Perillo T, Ugga L, Petretta M (2020) Machine learning in oncology a clinical appraisal. Cancer Lett 481:55\u201362","journal-title":"Cancer Lett"},{"key":"5592_CR13","unstructured":"The Chinese Clinical Guidance for COVID-19 Pneumonia Diagnosis and Treatment(7th version)"},{"key":"5592_CR14","doi-asserted-by":"publisher","first-page":"1915","DOI":"10.1002\/jmv.25889","volume":"92","author":"Q Zhao","year":"2020","unstructured":"Zhao Q, Meng M, Kumar R et al (2020) The impact of COPD and smoking history on the severity of Covid-19: A systemic review and meta-analysis. J Med Virol 92:1915\u20131921","journal-title":"J Med Virol"},{"issue":"18","key":"5592_CR15","doi-asserted-by":"publisher","first-page":"1708","DOI":"10.1056\/NEJMoa2002032","volume":"382","author":"WJ Guan","year":"2020","unstructured":"Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, Du B, Li LJ, Zeng G, Yuen KY, Chen RC, Tang CL, Wang T, Chen PY, Xiang J, Li SY, Wang JL, Liang ZJ, Peng YX, Wei L, Liu Y, Hu YH, Peng P, Wang JM, Liu JY, Chen Z, Li G, Zheng ZJ,Qiu SQ, Luo J, Ye CJ, Zhu SY, Zhong NS; China Medical Treatment Expert Group for Covid-19 (2020) Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 382(18):1708\u20131720. https:\/\/doi.org\/10.1056\/NEJMoa2002032","journal-title":"N Engl J Med"},{"issue":"10223","key":"5592_CR16","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1016\/S0140-6736(20)30183-5","volume":"395","author":"C Huang","year":"2020","unstructured":"Huang C, Wang Y, Li X et al (2020) Clinical features of patients infected with 2019 novel coronavirus in Wuhan. China Lancet 395(10223):497\u2013506","journal-title":"China Lancet"},{"issue":"10","key":"5592_CR17","doi-asserted-by":"publisher","first-page":"1902","DOI":"10.1002\/jmv.2588","volume":"92","author":"J Zhu","year":"2020","unstructured":"Zhu J, Ji P, Pang J, Zhong Z, Li H, He C, Zhang J, Zhao C (2020) Clinical characteristics of 3062 COVID-19 patients: a meta-analysis. J Med Virol 92(10):1902\u20131914. https:\/\/doi.org\/10.1002\/jmv.2588","journal-title":"J Med Virol"},{"issue":"10","key":"5592_CR18","doi-asserted-by":"publisher","first-page":"1733","DOI":"10.1002\/jmv.25819","volume":"92","author":"FA Lagunas-Rangel","year":"2020","unstructured":"Lagunas-Rangel FA (2020) Neutrophil-to-lymphocyte ratio and lymphocyte-to-C-reactive protein ratio in patients with severe coronavirus disease 2019 (COVID-19): a meta-analysis. J Med Virol 92(10):1733\u20131734","journal-title":"J Med Virol"},{"issue":"15","key":"5592_CR19","doi-asserted-by":"publisher","first-page":"762","DOI":"10.1093\/cid\/ciaa248","volume":"71","author":"C Qin","year":"2020","unstructured":"Qin C, Zhou L, Hu Z et al (2020) Dysregulation of immune response in patients with COVID-19 in Wuhan China. Clin Infect Dis 71(15):762\u2013768","journal-title":"Clin Infect Dis"},{"issue":"7","key":"5592_CR20","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.1002\/art.41285","volume":"72","author":"LA Henderson","year":"2020","unstructured":"Henderson LA, Canna SW, Schulert GS et al (2020) On the alert for cytokine storm: Immunopathology in COVID-19. Arthr Rheumatol 72(7):1059\u20131063","journal-title":"Arthr Rheumatol"},{"issue":"7","key":"5592_CR21","doi-asserted-by":"publisher","first-page":"791","DOI":"10.1002\/jmv.25770","volume":"92","author":"Y Gao","year":"2020","unstructured":"Gao Y, Li T, Han M et al (2020) Diagnostic utility of clinical laboratory data determinations for patients with the severe COVID-19. J Med Virol 92(7):791\u2013796","journal-title":"J Med Virol"},{"issue":"1","key":"5592_CR22","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.jaci.2020.04.006","volume":"146","author":"X Li","year":"2020","unstructured":"Li X, Xu S, Yu M et al (2020) Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allerg Clin Immunol 146(1):110\u2013118","journal-title":"J Allerg Clin Immunol"},{"issue":"1","key":"5592_CR23","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1615\/CritRevImmunol.v32.i1.30","volume":"32","author":"SS Iyer","year":"2012","unstructured":"Iyer SS, Cheng G (2012) Role of interleukin 10 transcriptional regulation in inflammation and autoimmune disease. Crit Rev Immunol 32(1):23\u201363","journal-title":"Crit Rev Immunol"},{"issue":"11","key":"5592_CR24","doi-asserted-by":"publisher","first-page":"1301","DOI":"10.1038\/nm1492","volume":"12","author":"DG Brooks","year":"2006","unstructured":"Brooks DG, Trifilo MJ, Edelmann KH, Teyton L, McGavern DB, Oldstone MB (2006) Interleukin-10 determines viral clearance or persistence in vivo. Nat Med 12(11):1301\u20131309","journal-title":"Nat Med"},{"key":"5592_CR25","doi-asserted-by":"crossref","unstructured":"Tong L, Du B, Liu R, Zhang L, Tan KC (2020) Hyperspectral Endmember Extraction by (\u03bc+ \u03bb) Multiobjective Differential Evolution Algorithm Based on Ranking Multiple Mutations, IEEE Transactions on Geoscience and Remote Sensing, 13 pages, online first.","DOI":"10.1109\/TGRS.2020.3004307"},{"key":"5592_CR26","first-page":"103246","volume":"282","author":"X Li","year":"2020","unstructured":"Li X, Du B, Xu C, Zhang Y, Zhang L, Tao D (2020) Robust learning with imperfect privileged information. ArtifIntell 282:103246","journal-title":"ArtifIntell"},{"issue":"12","key":"5592_CR27","doi-asserted-by":"publisher","first-page":"9976","DOI":"10.1109\/TGRS.2019.2930682","volume":"57","author":"B Du","year":"2019","unstructured":"Du B, Ru L, Wu C, Zhang L (2019) Unsupervised deep slow feature analysis for change detection in multi-temporal remote sensing images. IEEE Trans Geosci Remote Sens 57(12):9976\u20139992","journal-title":"IEEE Trans Geosci Remote Sens"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05592-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-020-05592-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05592-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T20:04:35Z","timestamp":1684440275000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-020-05592-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,5]]},"references-count":27,"journal-issue":{"issue":"18","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["5592"],"URL":"https:\/\/doi.org\/10.1007\/s00521-020-05592-1","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-38913\/v1","asserted-by":"object"}]},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,5]]},"assertion":[{"value":"27 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 December 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 January 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"We declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The study was approved by the institutional committee board of Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, and Universiti Brunei Darussalam Research Ethics Committee. All cases were anonymous in the final analysis.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and content to participate"}},{"value":"The requirement for informed consent was waived due to the retrospective nature of the analyses.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}