Abstract
Diabetes and its related consequences are some of the most alarming health problems the world is currently facing. Recent studies have shown that one-fourth of adults all over the world are overweight and more than one-tenth are obese. Diabetes is identified as a major risk factor for determining the severity of coronary artery disease (CAD). Diagnosing a heart disease is a very tedious task. In this paper, several attributes like age, BMI, glycated haemoglobin, triglyceride, total cholesterol, HDL, LDL, insulin resistance, smoker, alcoholic, and family diabetic history are identified as major causes for chronic diseases. We have explained how different attributes are related to each other and how various machine learning models are implicated and applied to them.
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Hemanth Reddy, K., Saranya, G. (2021). Prediction of Cardiovascular Diseases in Diabetic Patients Using Machine Learning Techniques. In: Hemanth, D., Vadivu, G., Sangeetha, M., Balas, V. (eds) Artificial Intelligence Techniques for Advanced Computing Applications. Lecture Notes in Networks and Systems, vol 130. Springer, Singapore. https://doi.org/10.1007/978-981-15-5329-5_28
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DOI: https://doi.org/10.1007/978-981-15-5329-5_28
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