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Data Analytics to Predict, Detect, and Monitor Chronic Autoimmune Diseases Using Machine Learning Algorithms: Preventing Diseases With the Power of Machine Learning

Data Analytics to Predict, Detect, and Monitor Chronic Autoimmune Diseases Using Machine Learning Algorithms: Preventing Diseases With the Power of Machine Learning

Jayashree M. Kudari
Copyright: © 2021 |Pages: 33
ISBN13: 9781799871880|ISBN10: 1799871886|ISBN13 Softcover: 9781799871897|EISBN13: 9781799871903
DOI: 10.4018/978-1-7998-7188-0.ch012
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MLA

M. Kudari, Jayashree. "Data Analytics to Predict, Detect, and Monitor Chronic Autoimmune Diseases Using Machine Learning Algorithms: Preventing Diseases With the Power of Machine Learning." Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease, edited by Manikant Roy and Lovi Raj Gupta, IGI Global, 2021, pp. 150-182. https://doi.org/10.4018/978-1-7998-7188-0.ch012

APA

M. Kudari, J. (2021). Data Analytics to Predict, Detect, and Monitor Chronic Autoimmune Diseases Using Machine Learning Algorithms: Preventing Diseases With the Power of Machine Learning. In M. Roy & L. Gupta (Eds.), Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease (pp. 150-182). IGI Global. https://doi.org/10.4018/978-1-7998-7188-0.ch012

Chicago

M. Kudari, Jayashree. "Data Analytics to Predict, Detect, and Monitor Chronic Autoimmune Diseases Using Machine Learning Algorithms: Preventing Diseases With the Power of Machine Learning." In Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease, edited by Manikant Roy and Lovi Raj Gupta, 150-182. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-7188-0.ch012

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Abstract

Developments in machine learning techniques for classification and regression exposed the access of detecting sophisticated patterns from various domain-penetrating data. In biomedical applications, enormous amounts of medical data are produced and collected to predict disease type and stage of the disease. Detection and prediction of diseases, such as diabetes, lung cancer, brain cancer, heart disease, and liver diseases, requires huge tests and that increases the size of patient medical data. Robust prediction of a patient's disease from the huge data set is an important agenda in in this chapter. The challenge of applying a machine learning method is to select the best algorithm within the disease prediction framework. This chapter opts for robust machine learning algorithms for various diseases by using case studies. This usually analyzes each dimension of disease, independently checking the identified value between the limits to monitor the condition of the disease.

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