Analysis and Prediction Hormonal Effects of Metformin on PCOS in Mice using Machine Learning algorithms

polycystic ovarian syndrome (PCOS) forecasting is a useful tool for increasing woman’sawareness of their reproductive health. This illness is the most common endocrine disease in women ofreproductive age [۱]. In this study, machine learning algorithms are used to predict the PCOS. The siximportant classification models are applied to forecast PCOS model in mice. Considering the positiveeffects of metformin as a blood sugar-lowering and sex hormone-regulating drug that can improve thephysiological and histological activity of the ovary [۲]. the present study aims to investigate and predictthe therapeutic effect of metformin on important hormonal parameters and changes The amount ofblood sugar is to improve polycystic ovary syndrome with the help of machine learning [۳]. Modelswere compared and evaluated using statistical measures such as Accuracy, Balanced Accuracy, AUCROCCurve, and F۱ Score. Based on these evaluations, the best model was selected. kNN is thought tobe the best model for forecasting PCOS. The results demonstrate that In comparison to the patient group,all the studied parameters in PCOS improved following metformin treatment and theKneighborsclassifier’s Accuracy, Balanced Accuracy, AUC-ROC Curve, and F۱ Score are ۱.

کلیدواژه ها:

polycystic ovarian syndrome ، hyperandrogenism ، Hyperinsulinemia ، machine learning ، kNN