Diagnosis of Polycystic Ovary Syndrome Using XGBoost Algorithm

September 2024 in “ Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi ”

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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Diagnosis of Polycystic Ovary Syndrome Using XGBoost Algorithm

Research cited in this study

research Female Pattern Hair Loss and Polycystic Ovarian Syndrome: More Than Just Hirsutism

research Insulin Resistance, Hyperandrogenism, and Their Associated Symptoms as Precipitating Factors for Depression in Women With Polycystic Ovarian Syndrome

research Diagnostic Criteria for PCOS: Is There a Need for a Rethink?

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