Fembot AI: Intelligent PCOS Health Monitoring and Adaptive Personalized Care System

Abstract

Polycystic Ovary Syndrome (PCOS) is one of the most prevalent hormonal disorders affecting women of reproductive age, leading to long-term complications such as infertility, metabolic disorders, and mental health issues. Despite its widespread occurrence, early diagnosis and continuous monitoring remain challenging due to fragmented healthcare data, irregular symptom patterns, and limited personalized care mechanisms. This paper presents FemBot AI, an intelligent PCOS health monitoring and adaptive personalized care system that integrates data collection, preprocessing, analytics, conversational interaction, and decision support within a unified framework. The proposed system collects patient health data through questionnaires, lifestyle inputs, and historical medical records, processes it using machine learning–based analytics, and delivers personalized health insights through a conversational AI interface. The novelty of FemBot AI lies in its closed-loop health monitoring approach, where analytical insights dynamically adapt lifestyle recommendations, risk assessments, and user guidance. Experimental observations demonstrate improved accessibility, reduced dependency on manual clinical consultations for preliminary assessment, and enhanced user engagement through conversational interaction. The system provides a scalable and practical solution for intelligent women’s healthcare support.