Abstract
Decision making in case of medical diagnosis is a complicated process. A large number of overlapping structures and cases, and distractions, tiredness, and limitations with the human visual system can lead to inappropriate diagnosis. Machine learning (ML) methods have been employed to assist clinicians in overcoming these limitations and in making informed and correct decisions in disease diagnosis. Many academic papers involving the use of machine learning for disease diagnosis have been increasingly getting published. Hence, to determine the use of ML to improve the diagnosis in varied medical disciplines, a systematic review is conducted in this study. To carry out the review, six different databases are selected. Inclusion and exclusion criteria are employed to limit the research. Further, the eligible articles are classified depending on publication year, authors, type of articles, research objective, inputs and outputs, problem and research gaps, and findings and results. Then the selected articles are analyzed to show the impact of ML methods in improving the disease diagnosis. The findings of this study show the most used ML methods and the most common diseases that are focused on by researchers. It also shows the increase in use of machine learning for disease diagnosis over the years. These results will help in focusing on those areas which are neglected and also to determine various ways in which ML methods could be employed to achieve desirable results.
Highlights
Diagnosis is a way to classify medicines that are fundamental to how a medicine performs its part in society
The following section represents the ndings and results of the analysis and synthesis of the included articles. This result, which is the outcome of a systematic study of the papers, shows the ef ciency of applying Machine learning (ML) in disease diagnosis
We found which databases and publishers are publishing the greatest number of articles relating to ML in disease diagnosis
Summary
Diagnosis is a way to classify medicines that are fundamental to how a medicine performs its part in society. It is central to the medical system Appropriate and effective treatment usually involves a thorough diagnosis. The human method of scienti c judgment leading to correct diagnosis remains key to superior quality and healthy medical services even in this era of rapid technical transition [2]. The diagnostic error that harms patient does happen frequently. Multiple factors give rise to diagnostic errors, usually including both perceptual and system-related causes. Certain common factors involve misjudging the signi cance of observations, misinterpretation, errors originating from heuristics usage, and errors in judgment, when diagnostic hypotheses are developed and assessed [3,4,5]. There is a loss in improved patient care [6]
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