PCOD/PCOS HEALTH TRACKER: A SMART SYSTEM FOR MONITORING WOMEN’S HEALTH

Abstract: Polycystic Ovarian Disease (PCOD) and Polycystic Ovary Syndrome (PCOS) are common hormonal disorders affecting a large number of women, especially in their reproductive age. These conditions often lead to irregular menstrual cycles, weight fluctuations, acne, and other health complications. Due to busy lifestyles and lack of awareness, many women fail to monitor their symptoms regularly. This research proposes a PCOD/PCOS Health Tracker system that helps users record, monitor, and analyze their health data in a structured way. The system focuses on tracking menstrual cycles, symptoms, lifestyle habits, and basic health indicators. By providing a centralized platform, the proposed solution aims to improve awareness, encourage healthy habits, and support early detection of health issues. The system is designed to be user-friendly and accessible, making it suitable for everyday use.

Keywords: PCOD, PCOS, Machine Learning, Healthcare AI, Predictive Analytics, mHealth Application, Logistic Regression, Random Forest