A Survey on Early Heart Disease Detection using AI based Approach

With the development of machine intelligence and artificial intelligence, heart disease prediction models can be designed to avoid human errors, take precautionary measures and enhance the efficiency of detection in preliminary stages. Precise heart disease pre-diction can minimize mortality rate to a significant level and can provide clinical diagnosis support in the best possible manner. Certainly, these are the motivations to work in this domain and provide a detailed survey of heart disease prediction models. Several datasets and their attributes are analyzed to get the best possible insights related to heart disease. In this survey, several works of literature related to heart disease detection are taken based on machine learning, data mining and deep learning models from IEEE explore, Research Gate, PubMed, Google Scholar, Scopus, and Web of Science search engines. Most of the literature is recently published between 2015-2022. This literature survey identifies some important shortcomings of the state-of-artheart disease prediction models considering various methodologies and datasets. Finally, a precise heart disease estimation system based on machine intelligence algorithms can become a genuine option for improving patient health.