Diagnosis of Polycystic Ovary Syndrome Using XGBoost Algorithm

    Ömer Çağrı Yavuz
    TLDR XGBoost can effectively diagnose PCOS with 87% accuracy.
    This study focuses on diagnosing Polycystic Ovary Syndrome (PCOS) using the XGBoost algorithm, which is noted for its speed and reliability. The research utilized a dataset of 554 records from 10 hospitals in Kerala, India, sourced from Kaggle. The study aimed to analyze the impact of categorical data and dataset distribution on algorithm performance. By balancing the dataset, the XGBoost algorithm achieved an accuracy of 0.87. The findings suggest that XGBoost can significantly contribute to solving classification problems in healthcare, particularly for PCOS diagnosis.
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