Publication Name	World Journal of Diabetes
Manuscript ID	29074
Country	Iran

Received	2016-07-28 10:01
Peer-Review Started	2016-07-29 16:43
To Make the First Decision	2016-09-02 14:26
Return for Revision	2016-09-08 10:23
Revised	2016-10-12 05:33
Second Decision	2016-11-22 17:45
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2016-12-02 10:53
Articles in Press	2016-12-02 10:54
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2017-02-12 21:54
Publish the Manuscript Online	2017-02-15 11:49

ISSN	1948-9358 (online)
Open Access	This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
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Website	http://www.wjgnet.com

Category	Medical Informatics
Manuscript Type	Evidence-Based Medicine
Article Title	Fuzzy expert system for diagnosing diabetic neuropathy
Manuscript Source	Invited Manuscript
All Author List	Meysam Rahmani Katigari, Haleh Ayatollahi, Mojtaba Malek and Mehran Kamkar Haghighi
Funding Agency and Grant Number	Funding Agency Grant Number Iran university of Medical Sciences 541
Corresponding Author	Haleh Ayatollahi, Assistant Professor in Medical Informatics, Department of Health Information Management, School of Health Management and Information Sciences, IRAN University of Medical Sciences, No. 6, Shahid Yasami St., Vali-e-Asr St., Tehran 1996713883, Iran. ayatollahi.h@iums.ac.ir
Key Words	Expert systems; Fuzzy logic; Artificial inte­lligence; Diabetes mellitus; Diabetes complications; Diabetic neuropathies
Core Tip	In this study, an expert system was designed for diagnosing diabetic neuropathy. This system can help specialists to diagnose the disease more quickly by using the most common diagnostic parameters. Even general practitioners can use this system in remote areas to improve the quality of care for patients with diabetes. With it, patients will no longer need to undertake complex procedures, and the care plan can be applied at the right time.
Publish Date	2017-02-15 11:49
Citation	Rahmani Katigari M, Ayatollahi H, Malek M, Kamkar Haghighi M. Fuzzy expert system for diagnosing diabetic neuropathy. World J Diabetes 2017; 8(2): 80-88
URL	http://www.wjgnet.com/1948-9358/full/v8/i2/80.htm
DOI	http://dx.doi.org/10.4239/wjd.v8.i2.80

Full Article (PDF)	WJD-8-80.pdf
Full Article (Word)	WJD-8-80.doc
Manuscript File	29074-Review.docx
Answering Reviewers	29074-Answering reviewers.pdf
Audio Core Tip	29074-Audio core tip.mp3
Biostatistics Review Certificate	29074-Biostatistics statement.pdf
Conflict-of-Interest Disclosure Form	29074-Conflict-of-interest statement.pdf
Copyright License Agreement	29074-Copyright assignment.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	29074-Grant application form(s).pdf
Institutional Review Board Approval Form or Document	Institutional_Review_Board_Statement_20160727200420.docx
Non-Native Speakers of English Editing Certificate	29074-Language certificate.pdf
Peer-review Report	29074-Peer-review(s).pdf
Scientific Misconduct Check	29074-Scientific misconduct check.pdf
Scientific Editor Work List	29074-Scientific editor work list.pdf