DL based Heart Disease Prediction System using CT Scan Images

Deep learning (DL) holds a crucial role in medical imaging, with rapid integration into AI for diagnostics. Despite widespread use in medical research, DL encounters limitations in practical clinical diagnosis, particularly in efficient medical image analysis. Focusing on the diagnosis of cardiovascular disease (CVD) using AI and DL for predictive analysis from CT scan images, this article emphasizes the need for methodological development. It highlights the existing gap between DL's potential and its practical implementation in clinical settings. In the context of CVD diagnostics, the study addresses modular elements of DL, encompassing image classification, segmentation, and detection. The research identifies challenges arising from this paradigm shift and proposes solutions, paving the way for pre-operative computerized simulation planning and the application of suitable surgical intervention technologies.