DiabSense: early diagnosis of non-insulin-dependent diabetes mellitus using smartphone-based human activity recognition and diabetic retinopathy analysis with Graph Neural Network-Reference-Cited by-同舟云学术

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DiabSense: early diagnosis of non-insulin-dependent diabetes mellitus using smartphone-based human activity recognition and diabetic retinopathy analysis with Graph Neural Network

Published:2024-08-03 Issue:1 Volume:11 Page:
ISSN:2196-1115
Container-title:Journal of Big Data
language:en
Short-container-title:J Big Data

Author:

Alam Md Nuho Ul,Hasnine Ibrahim,Bahadur Erfanul Hoque,Masum Abdul Kadar Muhammad,Urbano Mercedes Briones,Vergara Manuel Masias,Uddin Jia,Ashraf Imran,Samad Md. Abdus

Funder

This research is funded by the European University of Atlantic.

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1186/s40537-024-00959-w.pdf

Reference93 articles.

1. International Diabetes Federation: IDF Diabetes Atlas, 10th ed. Brussels, Belgium. 2021. https://www.diabetesatlas.org

2. Gregg EW, Li Y, Wang J, Rios Burrows N, Ali MK, Rolka D, Williams DE, Geiss L. Changes in diabetes-related complications in the united states, 1990–2010. N Engl J Med. 2014;370(16):1514–23. https://doi.org/10.1056/NEJMoa1310799.

3. King P, Peacock I, Donnelly R. The uk prospective diabetes study (ukpds): clinical and therapeutic implications for type 2 diabetes. Br J Clin Pharmacol. 1999;48(5):643–8.

4. Simó-Servat O, Hernández C, Simó R. Diabetic retinopathy in the context of patients with diabetes. Ophthalmic Res. 2019;62(4):211–7.

5. Nentwich MM, Ulbig MW. Diabetic retinopathy-ocular complications of diabetes mellitus. World J Diabetes. 2015;6(3):489.

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