Optimized Polycystic Ovarian Disease Prognosis and Classification Using AI-Based Computational Approaches on Multi-Modality Data

    Kogilavani Shanmugavadivel, Murali Dhar M S, T R Mahesh, Taher Al‐Shehari, Nasser A Alsadhan, Temesgen Engida Yimer
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    Studysummary This study used machine learning models to analyze PCOS symptoms for early diagnosis, finding Support Vector Machine and VGG16 algorithms achieved high accuracy rates of 94.44% and 98.29% respectively.
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