Citation

Hasnat, Rehnuma and Al Mamun, Abdullah Sarwar and Musha, Ahmmad and Tahabilder, Anik (2023) A Review on Heart Diseases Prediction Using Artificial Intelligence. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 491. pp. 41-54. ISSN 1867-8211

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Abstract

Heart disease is one of the major concerns of this modern world. The insufficiency of the experts has made this issue a bigger concern. Diagnosing heart diseases at an early stage is possible with Artificial Intelligence (AI) techniques, which will lessen the needed number of experts. This paper has initially discussed different kinds of heart diseases and the importance of detecting them early. Two popular diagnosis systems for collecting data and their working function are then highlighted. Different types of Model architectures in the corresponding field are described. Firstly, the Support Vector Machine (SVM) machine learning algorithm is described, and secondly, popular deep learning model architecture such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), etc. are highlighted to detect heart disease. Finally, discussion, comparison, and future work are described. This article aims to clarify AI’s present and future state in medical technology to predict heart diseases.

Item Type:	Article
Uncontrolled Keywords:	Artificial Intelligence
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Management (FOM)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	01 Aug 2023 01:13
Last Modified:	01 Aug 2023 01:13
URII:	http://shdl.mmu.edu.my/id/eprint/11583

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