|A Comparison between Fuzzy Type-2 and Type-1 Systems in Medical Decision Making: A Systematic Review|
|Azam Orooji1, Mostafa Langarizadeh1, Maryam Hassanzad2, Mohamad Reza Zarkesh3|
|1Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran- Iran
2Pediatric Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
3Department of Neonatology, School of Medicine,Tehran University of Medical Sciences,Tehran,Iran
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Keywords : Expert systems, Clinical decision support systems, Medical diagnosis, Type 2 fuzzy logic
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Objectives Fuzzy logic is a powerful tool for dealing with uncertainty and implemented in two ways, type-1 and type-2. Since, medical decision-making has always been associated with many uncertainties, expert systems(ESs) and decision support systems(DSSs), based on type-1 and type-2 fuzzy logic have been applied. The present study reviews different types of fuzzy ES/DSSin medical domain to investigate whether fuzzy type-2 performance is better than type-1.
Materials and Methods: A systematic review was conducted on PubMed, Web of sciences, Scopus, Embase, Medline and Science Direct databases. Articles which published between 2007 up to 2017 were evaluated independently by two reviewers for title, abstract and full text, respectively. Cases of disagreement were solved in a pair-work discussion. Finally based on inclusion criteria, 12 articles entered into the study. They were investigated in terms of purpose and application, architecture and structural detail, method of evaluation and the findings.
Results:Type-2 expert systems have a better diagnostic function than Type-1 systems and other different machine learning methods. Increasing the accuracy, precision and resistance to noise are some of the things that has been achieved in such systems using type-2 fuzzy logic.
Conclusions:Medical expert systems based on type-2 fuzzy logic are more capable to model uncertainty and ambiguity. Therefore, they could be used in different medical domain that need to make decisions under uncertain circumstances.
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