TAVR: An Automated Approach for Detection and Diagnosis Using Machine Learning Prediction Models

In a diseased person, the heart valve is replaced, Due to the advancement in technologies lifesaving medical devices are available. Plaque in the carotid artery can easily predict HD infirmity heart strokes and heart failure ( attacks) are some of the reasons behind this CA plaque, despite having no history of CVD in cardiovascular disease, the identification of blood flow through blood vessels is a complicated task. Premature degradation leads to high hydrodynamic loads due to the heart valve. The aortic valve is the main valve in the heart from where the blood supply is passed on to other arteries. Sometimes the CABG is operated in some cases, and deformation of a transcatheter aortic valve (TA V) is performed by putting a new artery for the circulation of blood flow. This type of prosthesis is a life-threatening procedure. This study aims to develop a model using machine learning. In the early stages, the aorta functioning (degradation and regurgitation) and replacement of the valve should be done at the right time. The frequent assessment of valve replacement could be automating the interpretation of blood flow. The aorta valve degradation could be identified by various symptoms shown in the patient's body, or angiography is a procedure that could be tested on a disease affecting the patient (asymptomatic severe ).In this study with the help of MI early detection of aortic stenosis gives a better outcome after the aortic valve replacement. ECG is the best way to identify patients with severe to moderate aortic stenosis patients.