Machine Learning Algorithms in Healthcare: A Literature Survey
Munira Ferdous, Jui Debnath, Narayan Ranjan Chakraborty
Abstract
Machine learning algorithms construct a remarkable contribution to predicting diseases. The generic purpose of this work is to help the researchers and practitioners to choose appropriate machine learning algorithm in health care. Previous research has shown that machine learning algorithms provide the best accuracy in diagnosing diseases but the accuracy of the algorithms and other related issues are hardly available in one complete paper. The necessary information has to be found in separate articles which is most frequently time-consuming and tedious. So, the objective of this work is to provide all the necessary information about the machine learning algorithms used in the healthcare sector. We generated a data table about machine learning algorithms accuracy for different diseases from the literature then finished this process step by step and systematized this survey paper. The output of this work produces a list of best machine learning algorithms with accuracy for predicting diseases. This output will help the researcher and practitioner to know about the contribution of machine learning algorithms in the field of health care with the accuracy of algorithms together in one complete paper.