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
DOI: 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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Background

What is Learning?

“Learning makes someone Intelligent and perform a task better”

  • •

    Learning is the process of acquiring new understanding, knowledge, behaviors, or skills through study, experience or being taught.

  • •

    The ability to learn is possessed by humans, birds and animals, even certain plants – Natural Learning.

  • •

    Now, computers/ machines are able to learn- Artificial Learning/ Machine Learning.

  • •

    Computers can learn and act like humans do, and improve their learning over time in autonomous fashion, by taking input data in the form of observations and real-world interactions.

What is Machine Learning?

Learning is the process of acquiring new understanding, knowledge, behaviors, or skills through study, experience or being taught. The ability to learn is possessed by humans, birds and animals, even certain plants – Natural Learning. Now, computers/ machines are able to learn- Artificial Learning/ Machine Learning. Computers can learn and act like humans, and improve their learning over time in independent mode by taking input data in the form of observations and real-world interactions.

Key Terms in this Chapter

KNN: K-nearest neighbor.

ECG: Electrocardiogram.

PCA: Principal component analysis.

CHD: Coronary heart disease.

AuC: Area under the curve.

SVM: Support vector machine.

Dt: Decision Tree.

BN: Bayesian networks (BN).

ROC: Receiver operating characteristic.

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