首页|National University of Singapore Reports Findings in Arthroplasty (Identifying w ho are unlikely to benefit from total knee arthroplasty using machine learning m odels)
National University of Singapore Reports Findings in Arthroplasty (Identifying w ho are unlikely to benefit from total knee arthroplasty using machine learning m odels)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Surgery - Arthroplasty is the subject of a report. According to news reporting from Singapore, Singapo re, by NewsRx journalists, research stated, “Identifying and preventing patients who are not likely to benefit long-term from total knee arthroplasty (TKA) woul d decrease healthcare expenditure significantly. We trained machine learning (ML ) models (image-only, clinical-data only, and multimodal) among 5720 knee OA pat ients to predict postoperative dissatisfaction at 2 years.” The news correspondents obtained a quote from the research from the National Uni versity of Singapore, “Dissatisfaction was defined as not achieving a minimal cl inically important difference in postoperative Knee Society knee and function sc ores (KSS), Short Form-36 Health Survey [SF-36, divided into a physical component score (PCS) and mental component score (MCS)] , and Oxford Knee Score (OKS). Compared to image-only models, both clinical-data only and multimodal models achieved superior performance at predicting dissatis faction measured by AUC, clinical-data only model: KSS 0.888 (0.866-0.909), SF-P CS 0.836 (0.812-0.860), SF-MCS 0.833 (0.812-0.854), and OKS 0.806 (0.753-0.859); multimodal model: KSS 0.891 (0.870-0.911), SF-PCS 0.832 (0.808-0.857), SF-MCS 0 .835 (0.811-0.856), and OKS 0.816 (0.768-0.863).”
SingaporeSingaporeAsiaArthroplastyCyborgsEmerging TechnologiesHealth and MedicineKnee ArthroplastyMachin e LearningSurgery
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