Insights and predictive analytics for heart disease using Python and machine learning

Abstract

In the era of big data, big data technology is increasingly permeating various medical fields, providing new technical support for the prediction and diagnosis of cardiovascular diseases. This study utilizes deep learning technology to analyze and model cardiac and cardiovascular data, developing a disease prediction model that features rapid detection and high accuracy. The model facilitates early identification and prognosis assessment of cardiovascular diseases, offering innovative approaches for clinical diagnosis and health management. The application of medical big data not only enhances the mining of disease-related characteristics but also supports the construction of medical knowledge graphs, driving the evolution of healthcare services toward intelligent and precision-oriented models. This research validates the effectiveness of big data technology in cardiovascular disease analysis, demonstrating significant potential for improving diagnostic efficiency and optimizing healthcare service systems.

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