ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1803.04337
  4. Cited By
Replication study: Development and validation of deep learning algorithm
  for detection of diabetic retinopathy in retinal fundus photographs
v1v2v3 (latest)

Replication study: Development and validation of deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs

12 March 2018
M. Voets
Kajsa Møllersen
L. A. Bongo
ArXiv (abs)PDFHTMLGithub (113★)

Papers citing "Replication study: Development and validation of deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs"

16 / 16 papers shown
Data Set Terminology of Deep Learning in Medicine: A Historical Review
  and Recommendation
Data Set Terminology of Deep Learning in Medicine: A Historical Review and Recommendation
S. Walston
Hiroshi Seki
H. Takita
Yasuhito Mitsuyama
Shingo Sato
Akifumi Hagiwara
Rintaro Ito
S. Hanaoka
Yukio Miki
D. Ueda
107
20
0
30 Apr 2024
AC-Norm: Effective Tuning for Medical Image Analysis via Affine
  Collaborative Normalization
AC-Norm: Effective Tuning for Medical Image Analysis via Affine Collaborative Normalization
Chuyan Zhang
Yuncheng Yang
Hao Zheng
Yun Gu
250
1
0
28 Jul 2023
A ResNet is All You Need? Modeling A Strong Baseline for Detecting
  Referable Diabetic Retinopathy in Fundus Images
A ResNet is All You Need? Modeling A Strong Baseline for Detecting Referable Diabetic Retinopathy in Fundus ImagesSymposium on Medical Information Processing and Analysis (MIPA), 2022
Tomás Castilla
Marcela S. Martínez
Mercedes Leguía
Ignacio Larrabide
J. Orlando
MedIm
176
5
0
06 Oct 2022
Deep Semi-Supervised and Self-Supervised Learning for Diabetic
  Retinopathy Detection
Deep Semi-Supervised and Self-Supervised Learning for Diabetic Retinopathy DetectionSymposium on Medical Information Processing and Analysis (MIPA), 2022
J. M. Ramos
Oscar J. Perdomo
Fabio A. González
110
5
0
04 Aug 2022
A deep learning model for classification of diabetic retinopathy in eye
  fundus images based on retinal lesion detection
A deep learning model for classification of diabetic retinopathy in eye fundus images based on retinal lesion detection
Melissa delaPava
Hernán Ríos
Francisco J. Rodríguez
Oscar J. Perdomo
Fabio A. González
MedIm
100
6
0
14 Oct 2021
On the Robustness of Pretraining and Self-Supervision for a Deep
  Learning-based Analysis of Diabetic Retinopathy
On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy
Vignesh Srinivasan
Nils Strodthoff
Jackie Ma
Alexander Binder
Klaus-Robert Muller
Wojciech Samek
OOD
155
7
0
25 Jun 2021
An Interpretable Multiple-Instance Approach for the Detection of
  referable Diabetic Retinopathy from Fundus Images
An Interpretable Multiple-Instance Approach for the Detection of referable Diabetic Retinopathy from Fundus ImagesScientific Reports (Sci Rep), 2021
Alexandros Papadopoulos
F. Topouzis
A. Delopoulos
122
36
0
02 Mar 2021
Fast Privacy-Preserving Text Classification based on Secure Multiparty
  Computation
Fast Privacy-Preserving Text Classification based on Secure Multiparty ComputationIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2021
A. Resende
Davis Railsback
Rafael Dowsley
Anderson C. A. Nascimento
Diego F. Aranha
205
22
0
18 Jan 2021
Objective Diagnosis for Histopathological Images Based on Machine
  Learning Techniques: Classical Approaches and New Trends
Objective Diagnosis for Histopathological Images Based on Machine Learning Techniques: Classical Approaches and New Trends
Naira Elazab
Hassan H. Soliman
Shaker El-Sappagh
S. Islam
Mohammed M Elmogy
187
23
0
10 Nov 2020
Smartphone-Based Test and Predictive Models for Rapid, Non-Invasive, and
  Point-of-Care Monitoring of Ocular and Cardiovascular Complications Related
  to Diabetes
Smartphone-Based Test and Predictive Models for Rapid, Non-Invasive, and Point-of-Care Monitoring of Ocular and Cardiovascular Complications Related to Diabetes
K. Chakravadhanula
28
9
0
25 Oct 2020
Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye
  Fundus Images
Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus ImagesInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2020
Adrian Galdran
José Dolz
H. Chakor
H. Lombaert
Ismail Ben Ayed
MedIm
275
33
0
01 Oct 2020
Hybrid Deep Learning Gaussian Process for Diabetic Retinopathy Diagnosis
  and Uncertainty Quantification
Hybrid Deep Learning Gaussian Process for Diabetic Retinopathy Diagnosis and Uncertainty Quantification
Santiago Toledo-Cortés
Melissa De La Pava
Oscar J. Perdomo
Fabio A. González
BDLMedIm
106
19
0
29 Jul 2020
Causal bootstrapping
Causal bootstrapping
Max A. Little
Reham Badawy
CML
135
21
0
21 Oct 2019
CrypTFlow: Secure TensorFlow Inference
CrypTFlow: Secure TensorFlow InferenceIEEE Symposium on Security and Privacy (IEEE S&P), 2019
Nishant Kumar
Mayank Rathee
Nishanth Chandran
Divya Gupta
Aseem Rastogi
Rahul Sharma
310
264
0
16 Sep 2019
Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted
  Inference
Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference
Edward Chou
Josh Beal
Daniel Levy
Serena Yeung
Albert Haque
Li Fei-Fei
211
221
0
25 Nov 2018
Towards Practical Verification of Machine Learning: The Case of Computer
  Vision Systems
Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems
Kexin Pei
Linjie Zhu
Yinzhi Cao
Junfeng Yang
Carl Vondrick
Suman Jana
AAML
318
108
0
05 Dec 2017
1
Page 1 of 1