A deep learning-based web application that predicts PCOS risk by fusing ultrasound image analysis (CNN) and clinical symptom data (CatBoost)
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Updated
Jan 22, 2026 - Jupyter Notebook
A deep learning-based web application that predicts PCOS risk by fusing ultrasound image analysis (CNN) and clinical symptom data (CatBoost)
A Streamlit-based machine learning app that predicts the likelihood of Polycystic Ovary Syndrome (PCOS) using health metrics. Built using an SVM classifier (SVC) and deployed on Streamlit Cloud for real-time predictions.
MyOvae, a deeply personalized and AI-driven wellness companion designed to empower individuals navigating the complexities of Polycystic Ovary Syndrome (PCOS). This isn't just another tracking app; it's an intelligent guide that transforms personal health data into actionable, holistic insights.
A comparative study of PCA, Genetic Algorithm, Particle Swarm Optimization, and Ant Colony Optimization for feature selection in PCOS prediction.
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