Abstract: Around the world, machine learning is utilized in a wide range of areas. The medical field is not an exception. Predicting whether there is a risk of heart diseases, issues with the loco motor system, and numerous other conditions can be significantly assisted by machine learning. Like that so information is predicted well in advance, it may offer physicians valuable insights that allow them to customize their diagnosis and treatment for each patient. We use machine learning techniques and methods for early prediction heart diseases in humans. In this project, we used machine learning techniques Logistic Regression & Decision Trees. We also suggest performing hybrid classification, as it can have numerous samples for both training and verifying the data.
Keywords: Machine learning, supervised learning, logistic regression, decision tree, python programming.
Cite:
Dr. Umesh Akare, Prof. Umme Ayeman Gani, Anushri Bhongade, Dhanashree Mure, Madhulika Chatterjee, Vanzuli Ramteke, "Heart Disease Prediction System Using Machine Learning", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 2, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.13315.
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DOI:
10.17148/IJARCCE.2024.13315
