Computer Aided Diagnostics System for Disease Prediction using Deep Learning

Abstract

Due to its negative effects on the central nervous system, brain stroke has recently risen to the top of the list of leading causes of death. Ischemic and hemorrhagic strokes, out of the several forms, mostly harm the central nervous system. However, by recognizing the type of stroke and responding to it quickly through smart health systems, the majority of stroke mortality can be avoided. The World Health Organisation (WHO) estimates that 87% of ischemic stroke cases, 10% of intracerebral haemorrhages, and 3% of subarachnoid haemorrhages impact the global population. Based on a patient's medical records, this study uses deep learning techniques to diagnose, categorise, and predict stroke. The ability of current studies to identify risk variables linked to different forms of stroke is limited.