Sakshi Loura
Vol. 10, Jul-Dec 2020
Abstract:
Information mining plays a vital part in the Healthcare industry. Information mining has been exceptionally useful in predicting disease, side effects, or any infection's stage/level of seriousness. Medical services businesses gather immense measures of information; in this way, AI saves time and ensures execution. This paper examined the different information mining strategies used in the medical care industry for coronary illness expectations and proposed a framework using Artificial Neural Networks (ANN). The Proposed System utilizes 8 clinical grades, such as sex, thallium test results, chest pain type, exang, age, and so on; the precision and key influencers for the proposed framework have also been examined. The most preferred supervised learning methods are Decision Tree (DT), Naive Bayes (NB) and Random Forest, and a similar investigation has been finished.