Modelling, simulation, and optimization of diabetes type II prediction using deep extreme learning machine-Reference-Cited by-同舟云学术

Modelling, simulation, and optimization of diabetes type II prediction using deep extreme learning machine

Published:2020-03-16 Issue:2 Volume:12 Page:125-138
ISSN:1876-1372
Container-title:Journal of Ambient Intelligence and Smart Environments
language:
Short-container-title:AIS

Author:

Rehman Abdur¹,Athar Atifa²,Khan Muhammad Adnan¹³,Abbas Sagheer¹,Fatima Areej¹,Atta-ur-Rahman ⁴,Saeed Anwaar⁵

Affiliation:

1. Department of Computer Science, National College of Business Administration & Economics, Lahore, Pakistan

2. Department of Computer Science, Comsats University Islamabad, Lahore Campus, Pakistan

3. Department of Computer Science, Lahore Garrison University, Lahore, Pakistan

4. Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam, 31441, Saudi Arabia

5. Department of Computer Science, Virtual University, Islamabad, Pakistan

Publisher

IOS Press

Subject

Software

Reference45 articles.

1. A method for classification using machine learning technique for diabetes;Aishwarya;International Journal of Engineering and Technology (IJET),2013

2. Application of data mining: Diabetes health care in young and old patients;Aljumah;Journal of King Saud University – Computer and Information Sciences,2013

3. Diagnosis and classification of diabetes mellitus;American Diabetes Association;Diabetes Care,2012

4. Blind Channel and Data Estimation Using Fuzzy Logic-Empowered Opposite Learning-Based Mutant Particle Swarm Optimization

5. Memetic computing based numerical solution to Troesch problem;Atta-ur-Rahman;Journal of Intelligent and Fuzzy Systems,2019

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