Abstract
Heart diseases include disordered functioning of heart which can be saved through early diagnosis. This diagnosis needs a lot of time to perceive the patient through an accurate approach for treatment. Technical advancements are a boon to healthcare domain for analyzing huge amounts of data generated by various hospitals. These data can be further preprocessed and filtered according to the disease analysis. In this paper, logistic regression (LR) and support vector machine (SVM) models are incorporated for effective prediction of heart disease. The results achieved are 93% accurate when the datasets are compared with SVM model.
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Challa, N.P., Shyam Mohan, J.S., Naga Badra Kali, M., Venkata Rama Raju, P. (2023). Intelligent Disease Analysis Using Machine Learning. In: Rao, B.N.K., Balasubramanian, R., Wang, SJ., Nayak, R. (eds) Intelligent Computing and Applications. Smart Innovation, Systems and Technologies, vol 315. Springer, Singapore. https://doi.org/10.1007/978-981-19-4162-7_12
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