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Intelligent Diagnosis of Heart Disease Based on Medical Feature Data

Author(s)

Feiyun Chen

Affiliation(s)

High School Affiliated to Fudan University, Shanghai, China

Abstract

Heart disease has a very high incidence rate worldwide and is the "number one killer" that threatens human life safety. In the traditional medical industry, doctors can only diagnose patients' conditions based on their knowledge reserves and their own accumulated experience. In order to reduce the risk of misjudgment due to the lack of experience of doctors in small and medium-sized hospitals, the classification algorithm of machine learning can be used to assist doctors in judging the patient's condition. Doctors can use the classification results given by machine learning as a reference opinion and combine their own experience to make more accurate diagnosis and treatment judgments for patients. Using the massive data of the medical system, integrating artificial intelligence technologies such as machine learning, and building an auxiliary medical decision-making system is a key step in promoting smart medicine, which can bring innovation and change to the medical field. Therefore, this paper studies the diagnosis of heart disease by combining medical feature data with artificial intelligence related methods.

Keywords

Heart Disease; Artificial Intelligence; Data Analysis; Intelligent Diagnosis; Big Data

References

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