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- W4290996965 abstract "The human heart is an important bodily organ. The death rate from heart disease is rising steadily in modern times. Due to several risk factors, detecting cardiovascular disease is extremely challenging such as abnormal pulse rate, high blood pressure, and many other factors. The healthcare sector now faces a problem in predicting cardiac disease. As a result, finding a trustworthy, accurate, and useful method to diagnose these illnesses in time for effective therapy is necessary. Large datasets generated by the healthcare sector employing machine learning algorithms, predictions and decision-making have been accomplished. The algorithms used are based on supervised learning. By using three algorithms of Machine Learning i.e., K-Nearest Neighbor, Decision Tree, Support Vector Machine and some of the results have been evaluated such as predicting the accuracy, confusion matrix, precision, and recall." @default.
- W4290996965 created "2022-08-13" @default.
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- W4290996965 date "2022-05-20" @default.
- W4290996965 modified "2023-10-09" @default.
- W4290996965 title "Cardiac Disease Prediction using Machine Learning Algorithms" @default.
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- W4290996965 doi "https://doi.org/10.1109/cises54857.2022.9844370" @default.
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