Deep neural networks to predict diabetic retinopathy-Reference-Cited by-同舟云学术

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Deep neural networks to predict diabetic retinopathy

Published:2020-04-24 Issue: Volume: Page:
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Gadekallu Thippa Reddy,Khare Neelu,Bhattacharya Sweta,Singh Saurabh,Maddikunta Praveen Kumar Reddy,Srivastava Gautam

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s12652-020-01963-7.pdf

Reference43 articles.

1. Abràmoff MD, Lou Y, Erginay A, Clarida W, Amelon R, Folk JC, Niemeijer M (2016) Improved automated detection of diabetic retinopathy on a publicly available dataset through integration of deep learning. Investig Ophthalmol Vis Sci 57(13):5200–5206

2. Antal B, Hajdu A (2014) An ensemble-based system for automatic screening of diabetic retinopathy. Knowl Based Syst 60:20–27

3. Bashir S, Qamar U, Khan FH (2016) Intellihealth: a medical decision support application using a novel weighted multi-layer classifier ensemble framework. J Biomed Inf 59:185–200

4. Bellemo V, Lim ZW, Lim G, Nguyen QD, Xie Y, Yip MY, Hamzah H, Ho J, Lee XQ, Hsu W et al (2019) Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in africa: a clinical validation study. Lancet Digital Health 1(1):e35–e44

5. Bhattacharya S, Kaluri R, Singh S, Alazab M, Tariq U et al (2020) A novel pca-firefly based xgboost classification model for intrusion detection in networks using gpu. Electronics 9(2):219

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