Integrated statistical and machine learning analysis provides insight into key influencing symptoms for distinguishing early‐onset type 2 diabetes-Reference-Cited by-同舟云学术

Integrated statistical and machine learning analysis provides insight into key influencing symptoms for distinguishing early‐onset type 2 diabetes

Published:2022-07-31 Issue:4 Volume:8 Page:281-295
ISSN:2589-0514
Container-title:Chronic Diseases and Translational Medicine
language:en
Short-container-title:Chronic Diseases and Translational Medicine

Author:

Wood David A.¹^ORCID

Affiliation:

1. DWA Energy Limited Lincoln UK

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cdt3.39

Reference43 articles.

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2. Diagnostic accuracy of tests for type 2 diabetes and prediabetes: A systematic review and meta-analysis

3. International Diabetes Federation. IDF Diabetes Atlas 10th Edition; 2021. Accessed April 15 2022.https://diabetesatlas.org/atlas/tenth-edition/

4. Diabetes Australia. Failure to detect type 2 diabetes early costing $700 million per year. 2018. Accessed April 15 2022.https://www.diabetesaustralia.com.au/mediarelease/failure-to-detect-type-2-diabetes-early-costing-700-million-per-year/

5. Early Detection and Treatment of Type 2 Diabetes Reduce Cardiovascular Morbidity and Mortality: A Simulation of the Results of the Anglo-Danish-Dutch Study of Intensive Treatment in People With Screen-Detected Diabetes in Primary Care (ADDITION-Europe)

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