Artificial Intelligence as a Bridge between Rehabilitation Sciences and Social Transformation in Postmenopausal Care

Abstract

Postmenopausal female often experiences pelvic floor dysfunction, 
musculoskeletal issues, reduced quality of life, and osteoporosis. 
Traditional approaches of physical therapy are helpful, but have some 
limitations such as social stigma, lack of resources, and personalized 
care, and access constraints. But in recent era, Artificial Intelligence (AI) 
is playing a pivotal role by bridging the gap between rehabilitation 
sciences and society, establishing an accessible, holistic, and patient
centered care particularly for the postmenopausal females. The purpose of this research is to explore how AI-driven treatment protocols can 
improve the clinical outcomes in postmenopausal women and to study 
the importance of AI in fostering and strengthening the social 
transformation in postmenopausal care. Motion tracking units and 
wearable devices improved the clinical outcomes and adherence to 
treatment and anticipate real time feedback. Further, predictive 
analytical models help the rehabilitationists and physical therapists in 
formulating preventive strategies based on musculoskeletal risks. This 
study implicated to encourage the use of AI tools in improving the 
health outcomes of postmenopausal females and eventually, reshaping 
the future of rehabilitation sciences and social wellbeing.