A Narrative Analysis Report on Heart Disease Prediction using Advanced Deep Learning Techniques in Smart Healthcare System

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Abstract

In recent years, the advancement of artificial intelligence (AI) and the gradual initiation of AI exploration in the medical industry have allowed people to recognize the promising potential of combining AI with healthcare. Data mining methods are being utilized efficiently in illness detection, which benefits health professionals. A vast amount of data is gathered from the health industry, and classification methods are used to identify new patterns. Heart disorders were chosen for diagnosis and categorization in this article. In this paper, an exhaustive analysis of certain common data mining algorithms is undertaken utilizing many datasets. The hot deep learning discipline, for example, has demonstrated increased potential in applications like as illness prediction and treatment response forecast. The study results will aid in understanding the primary data mining approaches and selecting the appropriate category of algorithms for heart disease analysis. This article provides several fundamental deep learning frameworks and common disorders, as well as a summary of deep learning prediction approaches for cardiac diseases. Point out several flaws in present illness prediction and provide a prognosis for future progress. It seeks to clarify the usefulness of deep learning in illness prophecy, as well as to highlight the high correlation among profession in terms of future growth. Deep learning approaches' unique feature extraction methods can still production an essential part in future medical inquiry.

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Keywords

Artificial intelligence; Data Mining; Deep Learning; Heart Disease Prediction; Healthcare Sector