Heart disease persists to be a major all-encompassing public health issue, contributing to infinite deaths and disabilities. Effective deterrent interventions and individualized situation programs depend on timely and exact risk prediction of myocardial infarction. Significant advancements in the field of cardiac affliction prediction have been created thanks to the development of machine intelligence techniques. This book chapter offers a all-encompassing analysis of the strengths, imperfections, and overall effectiveness of the various machine intelligence models used for heart disease indicator.
Author(s) Details:
Sunanda Budihal,
Department
of Computer Science, Shah Sogamal Peeraji Oswal Government First Grade College,
Muddebhihal, Vijayapura, Karnataka, India.
Sheetalrani
Rukmaji Kawale,
Department
of Computer Science, Karnataka State Akkamahadevi Women University, Vijayapura,
Karnataka, India.
Aparna Atul Junnarkar,
Department of Information Technology, Vishwakarma Institute of
Information Technology (VIIT), Pune, Maharashtra, India.
H. Faritha Begam,
Seethalakshmi Achi College for Women, Pallathur 630 107, Tamilnadu,
India.
Girish M.,
Department
of Computer Science and Engineering, Gopalan College of Engineering and
Management, Bangalore, Karnataka, India.
Please see the link here: https://stm.bookpi.org/ACST-V2/article/view/11926
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