Ovista: ML-Based Web Application for PCOS Detection

Abstract: Polycystic Ovary Syndrome (PCOS) is a common endocrine disorder affecting reproductive-age women, characterized by various symptoms and irregularities. This ovista proposes a comprehensive PCOS detection framework that combines numerical and image-based features. The numerical model uses a dual-pronged system: symptom-based prediction to identify PCOS presence, and parameter-based prediction to categorize its severity into low, medium, or severe. Built using machine learning algorithms, it offers an accurate diagnosis. Additionally, deep learning techniques are applied to analyze medical images for PCOS patterns, further enhancing detection accuracy. This multi-modal approach provides a holistic diagnostic tool, helping clinicians understand PCOS severity and enabling personalized treatment strategies.Ovista is a trusted companion in detecting and managing Polycystic Ovary Syndrome (PCOS). Designed with care and precision, Ovista leverages advanced technology to empower women by providing accurate insights into their health. The name Ovista is derived from the combination of "Ova" and "Vista". "Ova," meaning egg, represents the core focus on women's reproductive health, particularly issues related to the ovaries such as PCOS. "Vista" signifies vision or perspective, highlighting the platform’s mission to provide a clear and comprehensive understanding of health. Together, Ovista symbolizes a visionary approach to empowering women with insights and solutions for managing PCOS effectively.