Machine Learning-Based Explainable Automated Nonlinear Computation Scoring System for Health Score and an Application for Prediction of Perioperative Stroke: Retrospective Study.
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| Title: | Machine Learning-Based Explainable Automated Nonlinear Computation Scoring System for Health Score and an Application for Prediction of Perioperative Stroke: Retrospective Study. |
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| Authors: | Oh MY; Department of Neurology, Sejong General Hospital, Sejong General Hospital, Bucheon-si, Republic of Korea., Kim HS; Department of Medical Informatics, School of Medicine, Keimyung University, Daegu, Republic of Korea., Jung YM; Department of Obstetrics and Gynecology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea., Lee HC; Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.; Department of Anesthesiology and Pain Medicine, Seoul National University Hospital, Seoul, Republic of Korea., Lee SB; Department of Medical Informatics, School of Medicine, Keimyung University, Daegu, Republic of Korea., Lee SM; Department of Obstetrics and Gynecology, College of Medicine, Seoul National University, Seoul, Republic of Korea.; Department of Obstetrics and Gynecology, Seoul National University Hospital, Seoul, Republic of Korea.; Innovative Medical Technology Research Institute, Seoul National University Hospital, Seoul, Republic of Korea.; Institute of Reproductive Medicine and Population & Medical Big Data Research Center, Seoul National University, Seoul, Republic of Korea. |
| Source: | Journal of medical Internet research [J Med Internet Res] 2025 Mar 19; Vol. 27, pp. e58021. Date of Electronic Publication: 2025 Mar 19. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: JMIR Publications Country of Publication: Canada NLM ID: 100959882 Publication Model: Electronic Cited Medium: Internet ISSN: 1438-8871 (Electronic) Linking ISSN: 14388871 NLM ISO Abbreviation: J Med Internet Res Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1438-8871 |
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| DOI: | 10.2196/58021 |
