A Regression Analysis for Predicting Surgical Complications

A surgical complication is any undesirable and unexpected result of an operation. Surgical complications could be fatal to a patient if they are not detected earlier. One the factors that affect severity time between patient's diagnosis surgery. The might at risk doctor misdiagnoses them or concludes has no severe symptoms. This paper aims study correlation post-surgical conditions & duration with possible complications. Using regression analysis, research intends evaluate predictive possibilities early discovery these results reveal Gradient Boosting Regressor performs minimal error rate predicts almost all in line original data, measured across MAE, RMSE R2 scores 0.07, 0.11 0.98 respectively. In comparison Random Forest Decision Tree Regressor, 70-80% efficiently three major aforementioned metrics on average. Thus, presenting itself as valuable tool for finding correlations data intervention