Fuzzy logic approach for infectious disease diagnosis: A methodical evaluation, literature and classification

Goli Arji; Hossein Ahmadi; Mehrbakhsh Nilashi; Tarik A Rashid; Omed Hassan Ahmed; Nahla Aljojo; Azida Zainol

doi:10.1016/j.bbe.2019.09.004

Fuzzy logic approach for infectious disease diagnosis: A methodical evaluation, literature and classification

Biocybern Biomed Eng. 2019 Oct-Dec;39(4):937-955. doi: 10.1016/j.bbe.2019.09.004. Epub 2019 Sep 26.

Authors

Goli Arji¹, Hossein Ahmadi^{2

3}, Mehrbakhsh Nilashi^{4

5}, Tarik A Rashid⁶, Omed Hassan Ahmed^{7

8}, Nahla Aljojo⁹, Azida Zainol¹⁰

Affiliations

¹ School of Nursing and Midwifery, Health Information Technology Department, Saveh University of Medical Sciences, Iran.
² Halal Research Center of IRI, FDA, Tehran, Iran.
³ Department of Information Technology, University of Human Development, Sulaymaniyah, Iraq.
⁴ Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
⁵ Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
⁶ Computer Science and Engineering Department, University of Kurdistan Hewler, Erbil, Kurdistan, Iraq.
⁷ School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield, United Kingdom.
⁸ University of Human Development, College of Science and Technology, Department of Information Technology, Sulaymaniyah, Iraq.
⁹ College of Computer Science and Engineering, Department of Information Systems and Technology, University of Jeddah, Jeddah, Saudi Arabia.
¹⁰ Department of Software Engineering, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia.

Abstract

This paper presents a systematic review of the literature and the classification of fuzzy logic application in an infectious disease. Although the emergence of infectious diseases and their subsequent spread have a significant impact on global health and economics, a comprehensive literature evaluation of this topic has yet to be carried out. Thus, the current study encompasses the first systematic, identifiable and comprehensive academic literature evaluation and classification of the fuzzy logic methods in infectious diseases. 40 papers on this topic, which have been published from 2005 to 2019 and related to the human infectious diseases were evaluated and analyzed. The findings of this evaluation clearly show that the fuzzy logic methods are vastly used for diagnosis of diseases such as dengue fever, hepatitis and tuberculosis. The key fuzzy logic methods used for the infectious disease are the fuzzy inference system; the rule-based fuzzy logic, Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy cognitive map. Furthermore, the accuracy, sensitivity, specificity and the Receiver Operating Characteristic (ROC) curve were universally applied for a performance evaluation of the fuzzy logic techniques. This thesis will also address the various needs between the different industries, practitioners and researchers to encourage more research regarding the more overlooked areas, and it will conclude with several suggestions for the future infectious disease researches.

Keywords: Communicable disease; Disease diagnosis; Fuzzy logic; Infectious disease; Literature review.