Diagnosis of Polycystic Ovary Syndrome Using XGBoost Algorithm

    Ömer Çağrı Yavuz
    TLDR XGBoost can effectively diagnose PCOS with 87% accuracy.
    The study investigates the use of the XGBoost algorithm for diagnosing Polycystic Ovary Syndrome (PCOS) using a dataset of 554 records from 10 hospitals in Kerala, India. The algorithm achieved an accuracy of 0.87, demonstrating its potential effectiveness in healthcare classification problems, particularly for PCOS. The research also analyzed the influence of categorical data and dataset distribution on the algorithm's performance, focusing on symptoms like menstrual irregularities, hyperandrogenism, and metabolic abnormalities.
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