Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Surgery - Reoperation is the subject of a report. According to news reporting from Toronto, Canada, by NewsRx journalists, research stated, “Oncological resection and reconstruction involving the lower extremities commonly lead to reoperations that impact patien t outcomes and healthcare resources. This study aimed to develop a machine learn ing (ML) model to predict this reoperation risk.” The news correspondents obtained a quote from the research from the University o f Toronto, “This study was conducted according to TRIPOD + AI. Data from the PAR ITY trial was used to develop ML models to predict the 1-year reoperation risk f ollowing lower extremity oncological resection and reconstruction. Six ML algori thms were tuned and calibrated based on fivefold cross-validation. The best-perf orming model was identified using classification and calibration metrics. The po lynomial support vector machine (SVM) model was chosen as the best-performing mo del. During internal validation, the SVM exhibited an AUC-ROC of 0.73 and a Brie r score of 0.17. Using an optimal threshold that balances all quadrants of the c onfusion matrix, the SVM exhibited a sensitivity of 0.45 and a specificity of 0. 81. Using a high-sensitivity threshold, the SVM exhibited a sensitivity of 0.68 and a specificity of 0.68. Total operative time was the most important feature f or reoperation risk prediction.”
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