Early <scp>PCOS</scp> Detection: A Comparative Analysis of Traditional and Ensemble Machine Learning Models With Advanced Feature Selection

ABSTRACT PCOS (polycystic ovary syndrome) is a common hormonal disorder that affects many women during their reproductive years. It is marked by hormonal imbalances, leading to ovarian cysts, and can result in health issues such as infertility, diabetes, and even heart problems. Diagnosing PCOS accurately and early can be challenging, as it requires specific medical expertise. However, spotting PCOS promptly allows individuals to follow medical recommendations, which can lead to healthier lifestyles. In this study, we examined a dataset consisting of 541 patient records to enhance the detection of PCOS using advanced machine learning techniques. We established a data preprocessing pipeline that rigorously addressed missing values and identified outliers, while also normalizing the data to ensure it was ready for…