A fuzzy rule-based expert system for diagnosing cystic fibrosis

Journal Title: Electronic Physician - Year 2017, Vol 9, Issue 12

Abstract

BACKGROUND: Finding a valid diagnosis is mostly a prolonged process. Current advances in the sector of artificial intelligence have led to the appearance of expert systems that enrich the experiences and capabilities of doctors for making decisions for their patients. OBJECTIVE: The objective of this research was developing a fuzzy expert system for diagnosing Cystic Fibrosis (CF). METHODS: Defining the risk factors and then, designing the fuzzy expert system for diagnosis of CF were carried out in this cross-sectional study. To evaluate the performance of the proposed system, a dataset that corresponded to 70 patients with respiratory disease who were serially admitted to the CF Clinic in the Pediatric Respiratory Diseases Center, Masih Daneshvari Hospital in Tehran, Iran during August 2016 to January 2017 was considered. Whole procedures of system construction were implemented in a MATLAB environment. RESULTS: Results showed that the suggested system can be used as a strong diagnostic tool with 93.02% precision, 89.29% specificity, 95.24% sensitivity and 92.86% accuracy for diagnosing CF. There was also a good relationship between the user and the system through the appealing user interface. CONCLUSION: The system is equipped with information, knowledge, and expertise from certified specialists; hence, as a training tool it can be useful for new physicians. It is worth mentioning that the accomplishment of this project depends on advocacy of decision making in CF diagnosis. Nevertheless, it is expected that the system will reduce the number of false positives and false negatives in unusual cases

Authors and Affiliations

Maryam Hassanzad, Azam Orooji, Ali Valinejadi, Aliakbar Velayati

Keywords

Related Articles

Meanings of Health for Iranian Diabetic Patients: A qualitative study

INTRODUCTION: Health is an exclusive and subjective phenomenon, and one of the most important situations with regard to perception of health, arises when patients suffer from a chronic disease. This study was conducted w...

Lipid-lowering drugs (statins) and peripheral neuropathy

BACKGROUND AND AIM: Peripheral neuropathy is a disorder with often unknown causes. Some drugs, including statins, are proposed to be among the causes of peripheral neuropathy. This study aimed at evaluating this conditio...

Multiple bilateral pulmonary nodules masquerading as pulmonary metastasis; a case of nodular sarcoidosis

Sarcoidosis is a multi-system inflammatory disorder of unknown etiology that is manifested by the presence of non-caseating granulomas. Multiple pulmonary nodules are rare presentations of sarcoidosis. We report a case o...

The evaluation of serum homocysteine, folic acid, and vitamin B12 in patients complicated with preeclampsia

INTRODUCTION: Increased plasma homocysteine may be associated with adverse pregnancy outcomes, such as preeclampsia. The aim of this study was to determine the plasma homocysteine, serum folate, and vitamin B12 levels in...

Experiences of women regarding gaps in preconception care services in the Iranian reproductive health care system: A qualitative study

INTRODUCTION: Despite the beginnings of preconception care (PCC) delivery around a decade ago in Iran, there are still significant gaps in its service delivery. The purpose of this study was to explore the perceptions an...

Download PDF file
  • EP ID EP333514
  • DOI 10.19082/5974
  • Views 76
  • Downloads 0

How To Cite

Maryam Hassanzad, Azam Orooji, Ali Valinejadi, Aliakbar Velayati (2017). A fuzzy rule-based expert system for diagnosing cystic fibrosis. Electronic Physician, 9(12), 5974-5984. https://europub.co.uk/articles/-A-333514