Detection of Cardiovascular Disease using AI and ML: A Review
Keywords:
Cardiovascular disease, Artificial Intelligence, machine learning, comparative analysis, PCG, ECG, Deep LearningAbstract
In the 21st century according to statistics, the risk of cardiovascular disease has become more common and the death rate caused by it is increasing way more. Around 17.9 million lives are taken by CVDs each year. There are various reasons causing it but most importantly it is caused by not identifying it, hence it becomes a very important task for the human race to identify the CVDs and deal with the proper treatment so that the death dance caused by CVDs can be decreased and risk of it at an early age too. This work mainly aims to review and analyse various methods and approaches to detect the presence or absence of CVDs using AI and ML with accurate predictions. An artificial intelligence system for detecting heart disease from phonocardiogram (PCG) signals has been developed utilizing Artificial Neural Networks (ANN) algorithms and also by driving various AI algorithms on the given electrocardiogram (ECG) data of the patients we can predict the absence or presence of CVDs.
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