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Web-based Fuzzy Expert System for Diabetes Diagnosis

I.K. Mujawar1 , B.T. Jadhav2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-2 , Page no. 995-1000, Feb-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i2.9951000

Online published on Feb 28, 2019

Copyright © I.K. Mujawar, B.T. Jadhav . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: I.K. Mujawar, B.T. Jadhav, “Web-based Fuzzy Expert System for Diabetes Diagnosis,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.2, pp.995-1000, 2019.

MLA Style Citation: I.K. Mujawar, B.T. Jadhav "Web-based Fuzzy Expert System for Diabetes Diagnosis." International Journal of Computer Sciences and Engineering 7.2 (2019): 995-1000.

APA Style Citation: I.K. Mujawar, B.T. Jadhav, (2019). Web-based Fuzzy Expert System for Diabetes Diagnosis. International Journal of Computer Sciences and Engineering, 7(2), 995-1000.

BibTex Style Citation:
@article{Mujawar_2019,
author = {I.K. Mujawar, B.T. Jadhav},
title = {Web-based Fuzzy Expert System for Diabetes Diagnosis},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2019},
volume = {7},
Issue = {2},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {995-1000},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3781},
doi = {https://doi.org/10.26438/ijcse/v7i2.9951000}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i2.9951000}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3781
TI - Web-based Fuzzy Expert System for Diabetes Diagnosis
T2 - International Journal of Computer Sciences and Engineering
AU - I.K. Mujawar, B.T. Jadhav
PY - 2019
DA - 2019/02/28
PB - IJCSE, Indore, INDIA
SP - 995-1000
IS - 2
VL - 7
SN - 2347-2693
ER -

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Abstract

The proposed work presents an outline and execution of online fuzzy expert system for diabetes diagnosis (Web-FESDD). This work proposes a rule-based expert system where fuzzy logic was used. It was actualized online for the determination of diabetes disease using open source development environment. Doctors, diabetes experts and patients can utilize Web- FESDD for diabetes diagnosis as an intelligent diagnostic system. Fuzzy expert systems are able to handle imprecise data which occurs in process of disease diagnosis and treatment. Fuzzy Logic is highly suitable and applicable in designing expert systems in medicine context; especially in disease diagnosis procedure and in treatment plan. Open source programming advancement features and conditions were utilized to create and complete the proposed work.

Key-Words / Index Term

Dibetes Mellitus, Expert System, Fuzzy Logic, Fuzzy Expert System

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