A Study on the Behavior of Machine Learning Algorithms in Healthcare Datasets

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Author(s): Richa Singh (Bennett University, India), Shivani Gupta (Vellore Institute of Technology, Chennai, India)and Ninad Pravin Sabnis (Vellore Institute of Technology, Chennai, India)
Copyright: 2023
Pages: 28
Source title: Handbook of Research on Quantum Computing for Smart Environments
Source Author(s)/Editor(s): Amit Kumar Tyagi (National Institute of Fashion Technology, New Delhi, India)
DOI: 10.4018/978-1-6684-6697-1.ch021

Keywords: Engineering Science Reference / High Performance Computing / Knowledge Management and Library Science / Quantum Information & Computing

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Abstract

In this work, the authors have provided a study of various machine learning algorithms that makes use of datasets for diseases related to three different organs. Apart from the three separate organs, namely heart, kidney, and liver, this work also monitors the signs of two specific diseases: diabetes and breast cancer. It is possible that the number of patients that require constant attention may be far greater than the number of available doctors, and hence, the requirement of a system may arise wherein a machine may predict the severity of the person's condition based on his vitals and summon the required medical expertise. In this case, the prediction system might prove to be useful. Machine learning approaches have proven their capability in the prediction of disease diagnosis. The machine learning models are evaluated on datasets that include diabetes and breast cancer dataset and kidney, liver, and heart datasets to compare the accuracy of the models.

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A Study on the Behavior of Machine Learning Algorithms in Healthcare Datasets

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