Machine Learning Algorithms in Healthcare: A Literature Survey

Munira Ferdous, Jui Debnath, Narayan Ranjan Chakraborty
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引用次数: 18

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.
医疗保健中的机器学习算法:文献综述
机器学习算法在预测疾病方面做出了巨大贡献。这项工作的一般目的是帮助研究人员和从业者在医疗保健中选择合适的机器学习算法。先前的研究表明,机器学习算法在诊断疾病方面提供了最好的准确性,但算法的准确性和其他相关问题很难在一篇完整的论文中得到。必须在单独的文章中找到必要的信息,这通常是耗时和乏味的。因此,这项工作的目标是提供医疗保健领域使用的机器学习算法的所有必要信息。我们从文献中生成了不同疾病的机器学习算法精度数据表,然后逐步完成这一过程,并将这篇调查论文系统化。这项工作的结果产生了一个最佳机器学习算法列表,可以准确地预测疾病。该输出将帮助研究人员和实践者在一篇完整的论文中了解机器学习算法在医疗保健领域的贡献和算法的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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