The application of machine learning in the healthcare sector is a prominent area of research presently. Among these, there is significant potential in employing machine learning for predicting and treating heart disease. Hence, this study aims to explore the accuracy and application of machine learning models in predictive diagnosis and treatment of heart disease. This paper first presents commonly used machine learning algorithms within relevant fields, followed by gathering data and instances showcasing the use of machine learning in predicting and treating heart disease. Through data analysis, this study summarizes current cutting-edge development directions, trends, as well as the integration of machine learning algorithms into real medical processes. Finally, it concludes by summarizing the existing prospects and challenges faced by machine learning in predicting and treating heart disease. This paper can serve as a valuable source of inspiration and reference for researchers involved in related fields concerning heart disease prediction and treatment.
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