Research on the Influencing Factors of Heart Disease based on Binary Logit Regression
The heart is an important organ of the human body and plays an important role in the functioning of the human body. Heart disease has the greatest impact on the circulatory system. Patients will suffer from insufficient circulation blood supply, which will affect their health, including obvious chest tightness, shortness of breath, palpitations, pain in the precardiac area, discomfort in the precardiac area, accompanied by fatigue and difficulty in breathing. The study looked at clinical factors affecting heart disease. The dataset included 819 clinical cases and 12 variables, such as blood pressure, type of chest pain, etc. The target variable was whether a person had been diagnosed with heart disease. In this study, the accuracy of the first training set was about 88%, so the logistic regression results were acceptable. This model examines the factors that influence heart disease and can be useful in predicting heart disease. The conclusion shows that the risk of heart disease may be related to age, oldpeak, ChestPainType, MaxHR, FastingBS, cholesterol, ST slope and exercise angina pectoris.
Authors
- Haiyang Liang
- Xirui Ma
- Zhi-xiang Yang
- Yinuo Cheng (ORCID: https://orcid.org/0000-0002-0671-9193)
Institutions
- Xinjiang Production and Construction Corps (CN)
- Huzhou Vocational and Technical College (CN)
- Wuhan College (CN)
Publication Details
- Journal
- Highlights in Science Engineering and Technology
- Published
- 2024-08-15
- DOI
- https://doi.org/10.54097/86v3ha27
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00