Heart illness prediction using hybrid machine learning techniques
| Author(s) | : | Dibyanshu Chatterjee, Niveditha CA |
| Institution | : | Department of computer science and engineering, MS Ramaiah University of Applied Sciences, Bangalore |
| Published In | : | Vol. 7, Issue 12 — December 2020 |
| Page No. | : | 1-4 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Diseases can influence individuals both genuinely and intellectually, as contracting and living with anillness can adjust the influenced individual's viewpoint on life. A sickness that influences the parts of a living being,which isn't in view of any quick outer injury. Diseases are regularly known to be ailments that are identified with explicitindications and signs. The deadliest sicknesses in people are arteria coronaries disease (blood stream impediment),trailed by cerebrovascular sickness and lower respiratory contaminations. Coronary diseases are most eccentric andunexpectable. We can become ready to foresee the coronary illness utilizing AI strategy. The datasets are taken fromUCI store which is a public dataset. These prepared datasets are utilized for the expectation. Procedures like Decisiontree, Support Vector Machine, K Nearest Neighbor and Random Forest algorithms are utilized in the expectation ofcoronary illness and cross breed of these algorithms gives 94 % precision.
Dibyanshu Chatterjee, Niveditha CA, “Heart illness prediction using hybrid machine learning techniques”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 7, Issue 12, pp. 1-4, December 2020.
