Beyond the Cycle: PCOD/PCOS Health Monitoring and Wellness Management System

Abstract

Polycystic Ovary Syndrome (PCOS) is a complex and multifactorial condition that affects reproductive, metabolic, and overall wellness health. Its management extends beyond menstrual irregularities and involves symptoms, nutrition, physical activity, stress, lifestyle patterns, and environmental factors. With the increasing use of digital healthcare and artificial intelligence, various approaches have been proposed for PCOD/PCOS monitoring, mobile health applications, clinical assessment, and intelligent classification. This review paper presents a comparative analysis of five existing studies covering digital PCOS health tracking, mobile application evaluation, comparative clinical literature, explainable multimodal deep learning, and the evolutionary relationship between PCOS, lifestyle, and environmental factors. The reviewed studies are examined based on their research approach, working methodology, contributions, and limitations. The analysis shows that existing approaches address different aspects of PCOS independently, with digital systems primarily focusing on tracking, mobile applications emphasizing usability and information quality, clinical studies concentrating on disease understanding and management, and artificial intelligence approaches focusing mainly on classification. The review identifies a gap in comprehensive approaches that integrate continuous health monitoring, lifestyle assessment, intelligent analysis, and personalized wellness management. The findings emphasize the importance of moving beyond menstrual-cycle tracking toward a broader and more holistic approach to PCOD/PCOS health and wellness management.