• Suhas U
• Nikhil Babu S
• Soujanya N
• K Padma Priya

Artificial Intelligence (AI) is rapidly transforming healthcare diagnosticsby enabling early detection, precise analysis, and cost-effective management of diseases.This review focuses on AI's role in diagnosing osteoporosis, breast cancer, and kidneystones—three prevalent medical conditions. By utilizing Machine Learning (ML) andDeep Learning (DL) techniques, AI can analyze large volumes of clinical data, includingimaging scans and patient histories, with high accuracy. Techniques such as computeraided detection (CAD) and radiomics enhance medical imaging by identifying subtlepatterns that may be missed by traditional methods. A comparative evaluation of AImodels like support vector machines (SVM), convolutional neural networks (CNN),decision trees, and ensemble algorithms reveals their effectiveness in terms of diagnosticaccuracy, sensitivity, and efficiency. However, challenges such as data privacy concerns,algorithmic bias, and the scarcity of standardized annotated datasets continue to limitwidespread adoption. There is also a growing demand for explainable AI to ensureclinical transparency and trust. Integration of AI with electronic health records (EHRs)can further streamline diagnostics and decision-making processes. To fully realize AI’spotential, ethical regulations and interdisciplinary collaboration are crucial. This studyemphasizes the promising future of AI in diagnostics, provided that innovation isbalanced with responsible implementation and robust governance.

Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Healthcare Diagnostics, Osteoporosis, Medical Imaging, Computer-Aided Detection (CAD), Radiomics, Convolutional Neural Networks (CNN)

"AI-Driven Approaches for OsteoporosisDetection: A Deep Learning Perspective onMedical Imaging", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.c219-c225, May-2025, Available :http://www.jetir.org/papers/JETIR2505225.pdf

"AI-Driven Approaches for OsteoporosisDetection: A Deep Learning Perspective onMedical Imaging", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppc219-c225, May-2025, Available at : http://www.jetir.org/papers/JETIR2505225.pdf