An Optimized Recursive General Regression Neural Network Oracle for the Prediction and Diagnosis of Diabetes

Dana Bani-Hani; Pruthak Patel; Tasneem Alshaikh

An Optimized Recursive General Regression Neural Network Oracle for the Prediction and Diagnosis of Diabetes

Dana Bani-Hani * § M.S. Industrial Engineering PhD Industrial Engineering (ongoing degree pursuit)

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Pruthak Patel

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Tasneem Alshaikh

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State University of New York at Binghamton

An Optimized Recursive General Regression Neural Network Oracle for the Prediction and Diagnosis of Diabetes

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dana Bani-Hani, Pruthak Patel, Tasneem Alshaikh. 2019. "An Optimized Recursive General Regression Neural Network Oracle for the Prediction and Diagnosis of Diabetes". Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 19 (GJCST Volume 19 Issue D2).

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GJCST Volume 19 Issue D2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-D Classification I.2.6

Submission ReceivedDecember 11, 2018
Peer Review Double Blind
Handling Editor
Accepted January 2, 2019
Published January 15, 2019

Version of record

v1.2

Issue date

May 18, 2019

Language

English

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Article Matrices

Total Score: 173

Country: United States

Subject: Global Journal of Computer Science and Technology

Authors: Dana Bani-Hani, Pruthak Patel, Tasneem Alshaikh (PhD/Dr. count: 0)

View Count (all-time): 435

Total Views (Real + Logic): 2340

Total Downloads (simulated): 186

Publish Date: 2019 01, Tue

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Total Views: 2.3K

Total Downloads: 186

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