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Crowd disagreement about medical images is informative
v1v2 (latest)

Crowd disagreement about medical images is informative

21 June 2018
Veronika Cheplygina
J. Pluim
ArXiv (abs)PDFHTML

Papers citing "Crowd disagreement about medical images is informative"

14 / 14 papers shown
Title
KorNAT: LLM Alignment Benchmark for Korean Social Values and Common
  Knowledge
KorNAT: LLM Alignment Benchmark for Korean Social Values and Common Knowledge
Jiyoung Lee
Minwoo Kim
Seungho Kim
Junghwan Kim
Seunghyun Won
Hwaran Lee
Edward Choi
ALM
127
17
0
21 Feb 2024
Don't Label Twice: Quantity Beats Quality when Comparing Binary
  Classifiers on a Budget
Don't Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget
Florian E. Dorner
Moritz Hardt
74
4
0
03 Feb 2024
Noise Correction on Subjective Datasets
Noise Correction on Subjective Datasets
Uthman Jinadu
Yi Ding
36
1
0
01 Nov 2023
Confidence Contours: Uncertainty-Aware Annotation for Medical Semantic
  Segmentation
Confidence Contours: Uncertainty-Aware Annotation for Medical Semantic Segmentation
Andre Ye
Quan Ze Chen
Amy X. Zhang
UQCV
66
1
0
15 Aug 2023
Label-noise-tolerant medical image classification via self-attention and
  self-supervised learning
Label-noise-tolerant medical image classification via self-attention and self-supervised learning
Hongyang Jiang
Mengdi Gao
Yan Hu
Qi Ren
Zhaoheng Xie
Jiang-Dong Liu
NoLa
72
4
0
16 Jun 2023
The 'Problem' of Human Label Variation: On Ground Truth in Data,
  Modeling and Evaluation
The 'Problem' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation
Barbara Plank
93
100
0
04 Nov 2022
Calibrating Histopathology Image Classifiers using Label Smoothing
Calibrating Histopathology Image Classifiers using Label Smoothing
Jerry W. Wei
Lorenzo Torresani
Jason W. Wei
Saeed Hassanpour
38
1
0
28 Jan 2022
Dealing with Disagreements: Looking Beyond the Majority Vote in
  Subjective Annotations
Dealing with Disagreements: Looking Beyond the Majority Vote in Subjective Annotations
Aida Mostafazadeh Davani
Mark Díaz
Vinodkumar Prabhakaran
93
315
0
12 Oct 2021
Co-Correcting: Noise-tolerant Medical Image Classification via mutual
  Label Correction
Co-Correcting: Noise-tolerant Medical Image Classification via mutual Label Correction
Jiarun Liu
Ruirui Li
Chuan Sun
OODNoLaVLM
66
33
0
11 Sep 2021
ENHANCE (ENriching Health data by ANnotations of Crowd and Experts): A
  case study for skin lesion classification
ENHANCE (ENriching Health data by ANnotations of Crowd and Experts): A case study for skin lesion classification
Ralf Raumanns
Gerard Schouten
Max Joosten
J. Pluim
Veronika Cheplygina
66
6
0
27 Jul 2021
Multi-task Ensembles with Crowdsourced Features Improve Skin Lesion
  Diagnosis
Multi-task Ensembles with Crowdsourced Features Improve Skin Lesion Diagnosis
Ralf Raumanns
Elif K Contar
Gerard Schouten
Veronika Cheplygina
14
0
0
28 Apr 2020
A Survey of Crowdsourcing in Medical Image Analysis
A Survey of Crowdsourcing in Medical Image Analysis
S. Ørting
Andrew Doyle
A. Hilten
Matthias Hirth
Oana Inel
C. Madan
Panagiotis Mavridis
Helen Spiers
Veronika Cheplygina
81
71
0
25 Feb 2019
Precise Proximal Femur Fracture Classification for Interactive Training
  and Surgical Planning
Precise Proximal Femur Fracture Classification for Interactive Training and Surgical Planning
Amelia Jiménez-Sánchez
Anees Kazi
Shadi Albarqouni
C. Kirchhoff
P. Biberthaler
Nassir Navab
S. Kirchhoff
Diana Mateus
28
33
0
04 Feb 2019
Empirical Methodology for Crowdsourcing Ground Truth
Empirical Methodology for Crowdsourcing Ground Truth
Anca Dumitrache
Oana Inel
Benjamin Timmermans
Carlos Martinez-Ortiz
Robert-Jan Sips
Lora Aroyo
Chris Welty
HILM
122
17
0
24 Sep 2018
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