Heart disease is a chronic disease which is not infectious but has high mortality in clinic. It is difficult to be accurately analyzed by traditional medical decision-making and diagnosis methods. With the emergence of a large number of clinical diagnosis, treatment and examination reports and network electronic medical record data, information technology provides a large number of data basis for interventional medical diagnosis and auxiliary medical pathological diagnosis. Based on plenty of data for clinical diagnosis and treatment for effective extraction and processing, machine learning algorithms can make accurate diagnosis for heart diseases, predict the probability of disease disease cases and patients, and combined with relevant professional knowledge, in the field of balancing potential data analysis and processing, in order to get better disease diagnosis, improve disease prevention, diagnosis and research status.

Yang Sun. The Classification of Heart Disease Based on Artificial Network. Frontiers in Medical Science Research (2023) Vol. 5, Issue 6: 49-54. https://doi.org/10.25236/FMSR.2023.050609.

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