Repository of Research and Investigative Information

Repository of Research and Investigative Information

Ilam University of Medical Sciences

Developing a clinical decision support system based on the fuzzy logic and decision tree to predict colorectal cancer

Tue Aug 16 11:48:03 2022

(2021) Developing a clinical decision support system based on the fuzzy logic and decision tree to predict colorectal cancer. Medical journal of the Islamic Republic of Iran. p. 44. ISSN 1016-1430 (Print) 1016-1430 (Linking)

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Official URL: https://www.ncbi.nlm.nih.gov/pubmed/34268232

Abstract

Background: Colorectal Cancer (CRC) is the most prevalent digestive system- related cancer and has become one of the deadliest diseases worldwide. Given the poor prognosis of CRC, it is of great importance to make a more accurate prediction of this disease. Early CRC detection using computational technologies can significantly improve the overall survival possibility of patients. Hence this study was aimed to develop a fuzzy logic-based clinical decision support system (FL-based CDSS) for the detection of CRC patients. Methods: This study was conducted in 2020 using the data related to CRC and non-CRC patients, which included the 1162 cases in the Masoud internal clinic, Tehran, Iran. The chi-square method was used to determine the most important risk factors in predicting CRC. Furthermore, the C4.5 decision tree was used to extract the rules. Finally, the FL-based CDSS was designed in a MATLAB environment and its performance was evaluated by a confusion matrix. Results: Eleven features were selected as the most important factors. After fuzzification of the qualitative variables and evaluation of the decision support system (DSS) using the confusion matrix, the accuracy, specificity, and sensitivity of the system was yielded 0.96, 0.97, and 0.96, respectively. Conclusion: We concluded that developing the CDSS in this field can provide an earlier diagnosis of CRC, leading to a timely treatment, which could decrease the CRC mortality rate in the community.

Item Type: Article
Creators:
CreatorsEmail
Nopour, R.UNSPECIFIED
Shanbehzadeh, M.UNSPECIFIED
Kazemi-Arpanahi, H.UNSPECIFIED
Keywords: Artificial intelligence Crc Colorectal cancer Fuzzy logic Risk analysis Screening
Divisions:
Page Range: p. 44
Journal or Publication Title: Medical journal of the Islamic Republic of Iran
Journal Index: Pubmed
Volume: 35
Identification Number: https://doi.org/10.47176/mjiri.35.44
ISSN: 1016-1430 (Print) 1016-1430 (Linking)
Depositing User: مهندس مهدی شریفی
URI: http://eprints.medilam.ac.ir/id/eprint/3634

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