Deep learning for diabetic retinopathy detection and classification Using Long Short-Term Memory (LSTM)-Reference-Cited by-同舟云学术

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Deep learning for diabetic retinopathy detection and classification Using Long Short-Term Memory (LSTM)

Published:2024-03-22 Issue: Volume: Page:1-7
ISSN:
Container-title:2024 4th International Conference on Data Engineering and Communication Systems (ICDECS)
language:
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Author:

Kumar M. Prema¹,Goud D. Srinivas²,Sankar S.³,Kumar S. Sharath⁴

Affiliation:

1. Shri Vishnu Engineering College for Women(A),Department of Electronics and Communication Engineering,Bhimavaram,Andhra Pradesh,India

2. Vignana Bharathi Institute of Technology,Department of Computer Science and Engineering,Andhra Pradesh,India

3. Saveetha Institute of Medical and Technical Sciences,Saveetha School of Engineering,Department of Computer Science and Engineering,Chennai,India

4. RMD Engineering College, Kavaraipettai,Department of Computer Science and Engineering,Tiruvallur,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10502390/10502383/10502810.pdf?arnumber=10502810

Reference15 articles.

1. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition

2. Epidemiology of type 2 diabetes in India

3. Impact of severity of diabetic retinopathy on quality of life in type 2 Indian diabetic patients

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