Budihal, Sunanda and Kawale, Sheetalrani Rukmaji and Junnarkar, Aparna Atul and Begam, H. Faritha and M., Girish (2023) A Comparative Study of Machine Learning Models for Heart Disease Prediction. In: Advances and Challenges in Science and Technology Vol. 2. B P International (a part of SCIENCEDOMAIN International), pp. 59-71. ISBN Dr. Guang Yih Sheu Advances and Challenges in Science and Technology Vol. 2 09 20 2023 09 20 2023 9788119761432 B P International (a part of SCIENCEDOMAIN International) 10.9734/bpi/acst/v2 https://stm.bookpi.org/ACST-V2/issue/view/1187
Full text not available from this repository.Abstract
Heart disease continues to be a major global public health issue, contributing to innumerable deaths and disabilities. Effective preventive interventions and individualized treatment programs depend on timely and precise risk prediction of heart disease. Significant advancements in the field of cardiac disease prediction have been made thanks to the development of machine learning techniques. This book chapter offers a thorough analysis of the strengths, flaws, and overall effectiveness of the various machine learning models used for heart disease prediction.
| Item Type: | Book Section |
|---|---|
| Subjects: | Euro Archives > Computer Science |
| Depositing User: | Managing Editor |
| Date Deposited: | 05 Oct 2023 07:40 |
| Last Modified: | 05 Oct 2023 07:40 |
| URI: | http://publish7promo.com/id/eprint/3148 |
Actions (login required)
- View Item