AI-Driven Early Detection of Polycystic Ovary Syndrome via Follicle Count
This study develops machine learning models for early Polycystic Ovary Syndrome prediction using a structured clinical dataset with 42 features and 542 patient records and demonstrates that ensemble models can effectively capture non-linear feature interactions in clinical data.
D. Thota, A. Mahesha, M. F. Khasim et al.
· medRxiv · 0 citations