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- W4285220261 abstract "Health monitoring in humans is very important. This monitoring can be done in different people from embryonic period to adulthood. A healthy fetal will lead to a healthy baby. For this purpose, health assessment methods are used from the fetal to adulthood. One of the most common methods of assessing health at different times is to use clinical signs and data. Measuring heart rate, blood pressure, temperature, and other symptoms can help monitor health. However, there are usually errors in human predictions. Data mining is a technique for identifying and diagnosing diseases, categorizing patients in disease management, and finding patterns to diagnose patients more quickly and prevent complications. It could be a great help. Increasing the accuracy of diagnosis, reducing costs, and reducing human resources in the medical sector have been proven by researchers as the benefits of introducing data mining in medical analysis. In this paper, data mining methods will be introduced to diagnose and monitor health in individuals with various heart diseases. Heart disease will be evaluated to make the study more comprehensive, including fetal health diagnosis, arrhythmias, and machine learning data mining angiography. Attempts are made to introduce the relevant database in each disease and to evaluate the desired methods in health monitoring." @default.
- W4285220261 created "2022-07-14" @default.
- W4285220261 creator A5011015801 @default.
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- W4285220261 creator A5015196852 @default.
- W4285220261 creator A5077021387 @default.
- W4285220261 creator A5092307485 @default.
- W4285220261 date "2022-01-01" @default.
- W4285220261 modified "2023-10-15" @default.
- W4285220261 title "Health Monitoring Methods in Heart Diseases Based on Data Mining Approach: A Directional Review" @default.
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