INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · Oct 2026
OsteoAI: A Review of Explainable Artificial Intelligence, Osteoporosis Risk Prediction and Preventive Lifestyle Simulation
By Kosurkar S, Sarode PS, Ramteke A et al.
Osteoporosis is a long-term skeletal condition in which bone strength decreases and the likelihood of fragility fractures rises.Because the condition can develop without noticeable symptoms, identifying people at elevated risk before a fracture occurs is an important preventive goal.Conventional assessment commonly depends on bone mineral density and established clinical risk tools, although access to screening is not uniform across healthcare settings.Recent studies have examined machine learning (ML), deep learning, medical imaging, and explainable artificial intelligence (XAI) for osteoporosis classification and fracture-risk estimation.This review considers these developments with emphasis on clinical and lifestyle information, interpretable predictions, and decisionsupport applications.Existing reviews show encouraging results from AI-based methods, but they also point to concerns involving dataset variation, external validation, reporting standards, interpretability, and integration into clinical practice.Building on this evidence, the proposed OsteoAI approach combines routine clinical and lifestyle inputs with explainable ML, risk categories, personalized preventive suggestions, and lifestyle-based "what-if" simulation.The proposed system is presented as a projectlevel decision-support direction and not as a substitute for professional diagnosis.