Artificial Intelligence-based Learning Techniques for Diabetes Prediction: Challenges and Systematic Review-Reference-Cited by-同舟云学术

Artificial Intelligence-based Learning Techniques for Diabetes Prediction: Challenges and Systematic Review

Published:2020-10-06 Issue:6 Volume:1 Page:
ISSN:2662-995X
Container-title:SN Computer Science
language:en
Short-container-title:SN COMPUT. SCI.

Author:

Kaul Surabhi,Kumar Yogesh^ORCID

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s42979-020-00337-2.pdf

Reference37 articles.

1. Huang GB, Zhu QY, Siew CK, et al. Extreme learning machine: theory and applications. Neurocomputing. 2006;70:489–501.

2. Al Jarullah AA. Decision tree discovery for the diagnosis of type II diabetes. In: 2011 International conference on innovations in information technology. IEEE; 2011, pp. 303–7.

3. Anderson JP, et al. Reverse engineering and evaluation of prediction models for progression to type 2 diabetes: an application of machine learning using electronic health records. J Diabetes SciTechnol. 2016;10:6–18.

4. Bhargava N, Dayma S, Kumar A, Singh P. An approach for classification using simple CART algorithm in WEKA. In: 2017 11th international conference on intelligent systems and control (ISCO). IEEE; 2017. pp. 212–6.

5. Dagliati A, et al. Machine learning methods to predict diabetes complications. J Diabetes SciTechnol. 2018;12:295–302.

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Glycated hemoglobin (HbA1c) and biofluid-based diagnosis in diabetes: A comprehensive review;Journal of Electroanalytical Chemistry;2024-06

2. Early Detection of Type-2 Diabetes Mellitus using Machine Learning based Prediction Models;2024 11th International Conference on Computing for Sustainable Global Development (INDIACom);2024-02-28

3. Identifying Diabetes Related-Complications in a Real-World Free-Text Electronic Medical Records in Hebrew Using Natural Language Processing Techniques;Journal of Diabetes Science and Technology;2024-01-30

4. Need for an Artificial Intelligence-based Diabetes Care Management System in India and the United States;Health Services Research and Managerial Epidemiology;2024-01

5. Clinical applications of artificial intelligence in diabetes management: A bibliometric analysis and comprehensive review;Informatics in Medicine Unlocked;2024