Advancements in early detection of diabetes and diabetic retinopathy screening using artificial intelligence
Author:
Affiliation:
1. ECE, Nehru Institute of Engineering and Technology 1 , Coimbatore, T,N, India
2. Agricultural Engineering, Nehru Institute of Technology 2 , Coimbatore, T,N, India
Abstract
Publisher
AIP Publishing
Subject
General Physics and Astronomy
Link
https://pubs.aip.org/aip/adv/article-pdf/doi/10.1063/5.0172226/18201653/115307_1_5.0172226.pdf
Reference33 articles.
1. Population-level prediction of type 2 diabetes from claims data and analysis of risk factors;Big Data,2015
2. Deep patient: An unsupervised representation to predict the future of patients from the electronic health records;Sci. Rep.,2016
3. Can machine-learning improve cardiovascular risk prediction using routine clinical data?;PLoS One,2017
4. Machine learning methods to predict diabetes complications;J. Diabetes Sci. Technol.,2018
5. Automated identification of diabetic retinopathy using deep learning;Ophthalmology,2017
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