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Hidden Stratification Causes Clinically Meaningful Failures in Machine
  Learning for Medical Imaging

Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging

27 September 2019
Luke Oakden-Rayner
Jared A. Dunnmon
G. Carneiro
Christopher Ré
    OOD
ArXivPDFHTML

Papers citing "Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging"

50 / 163 papers shown
Title
WBCAtt: A White Blood Cell Dataset Annotated with Detailed Morphological
  Attributes
WBCAtt: A White Blood Cell Dataset Annotated with Detailed Morphological Attributes
Satoshi Tsutsui
Winnie Pang
Bihan Wen
37
14
0
23 Jun 2023
Simple and Fast Group Robustness by Automatic Feature Reweighting
Simple and Fast Group Robustness by Automatic Feature Reweighting
Shi Qiu
Andres Potapczynski
Pavel Izmailov
A. Wilson
OOD
75
54
0
19 Jun 2023
Concept Extrapolation: A Conceptual Primer
Concept Extrapolation: A Conceptual Primer
Matija Franklin
Rebecca Gorman
Hal Ashton
Stuart Armstrong
18
1
0
19 Jun 2023
Towards trustworthy seizure onset detection using workflow notes
Towards trustworthy seizure onset detection using workflow notes
Khaled Kamal Saab
Siyi Tang
Mohamed Taha
Christopher Lee-Messer
Christopher Ré
D. Rubin
19
4
0
14 Jun 2023
Agnostic Multi-Group Active Learning
Agnostic Multi-Group Active Learning
Nick Rittler
Kamalika Chaudhuri
13
1
0
02 Jun 2023
A Novel Strategy for Improving Robustness in Computer Vision
  Manufacturing Defect Detection
A Novel Strategy for Improving Robustness in Computer Vision Manufacturing Defect Detection
A. M. Mezher
A. Marble
UQCV
AAML
OOD
24
3
0
16 May 2023
"Nothing Abnormal": Disambiguating Medical Reports via Contrastive
  Knowledge Infusion
"Nothing Abnormal": Disambiguating Medical Reports via Contrastive Knowledge Infusion
Zexue He
An Yan
Amilcare Gentili
Julian McAuley
Chun-Nan Hsu
MedIm
35
2
0
15 May 2023
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance
  Between Data Subpopulations
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations
Weixin Liang
Yining Mao
Yongchan Kwon
Xinyu Yang
James Zou
OODD
42
3
0
04 May 2023
MaskSearch: Querying Image Masks at Scale
MaskSearch: Querying Image Masks at Scale
Dong He
Jieyu Zhang
Maureen Daum
Alexander Ratner
Magdalena Balazinska
VLM
42
2
0
03 May 2023
Are demographically invariant models and representations in medical
  imaging fair?
Are demographically invariant models and representations in medical imaging fair?
Eike Petersen
Enzo Ferrante
M. Ganz
Aasa Feragen
MedIm
51
10
0
02 May 2023
Data AUDIT: Identifying Attribute Utility- and Detectability-Induced
  Bias in Task Models
Data AUDIT: Identifying Attribute Utility- and Detectability-Induced Bias in Task Models
Michael F. Pavlak
Nathan G. Drenkow
N. Petrick
M. M. Farhangi
Mathias Unberath
MLAU
31
4
0
06 Apr 2023
Mitigating Source Bias for Fairer Weak Supervision
Mitigating Source Bias for Fairer Weak Supervision
Changho Shin
Sonia Cromp
Dyah Adila
Frederic Sala
29
2
0
30 Mar 2023
Problems and shortcuts in deep learning for screening mammography
Problems and shortcuts in deep learning for screening mammography
Trevor Tsue
Brent Mombourquette
Ahmed Taha
Thomas P. Matthews
Yen Nhi Truong Vu
Jason Su
16
1
0
29 Mar 2023
Distributionally Robust Optimization with Probabilistic Group
Distributionally Robust Optimization with Probabilistic Group
Soumya Suvra Ghosal
Yixuan Li
OOD
16
7
0
10 Mar 2023
Deep Hypothesis Tests Detect Clinically Relevant Subgroup Shifts in
  Medical Images
Deep Hypothesis Tests Detect Clinically Relevant Subgroup Shifts in Medical Images
Lisa M. Koch
C. M. Schurch
Christian F. Baumgartner
Arthur Gretton
Philipp Berens
OOD
34
1
0
08 Mar 2023
Group conditional validity via multi-group learning
Samuel Deng
Navid Ardeshir
Daniel J. Hsu
35
1
0
07 Mar 2023
fAIlureNotes: Supporting Designers in Understanding the Limits of AI
  Models for Computer Vision Tasks
fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Tasks
Steven Moore
Q. V. Liao
Hariharan Subramonyam
24
28
0
22 Feb 2023
Beyond Distribution Shift: Spurious Features Through the Lens of
  Training Dynamics
Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics
Nihal Murali
A. Puli
Ke Yu
Rajesh Ranganath
Kayhan Batmanghelich
AAML
43
8
0
18 Feb 2023
On (assessing) the fairness of risk score models
On (assessing) the fairness of risk score models
Eike Petersen
M. Ganz
Sune Holm
Aasa Feragen
FaML
23
20
0
17 Feb 2023
Zeno: An Interactive Framework for Behavioral Evaluation of Machine
  Learning
Zeno: An Interactive Framework for Behavioral Evaluation of Machine Learning
Ángel Alexander Cabrera
Erica Fu
Donald Bertucci
Kenneth Holstein
Ameet Talwalkar
Jason I. Hong
Adam Perer
28
48
0
09 Feb 2023
SkinCon: A skin disease dataset densely annotated by domain experts for
  fine-grained model debugging and analysis
SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained model debugging and analysis
Roxana Daneshjou
Mert Yuksekgonul
Zhuo Cai
R. Novoa
J. Zou
37
46
0
01 Feb 2023
Demystifying Disagreement-on-the-Line in High Dimensions
Demystifying Disagreement-on-the-Line in High Dimensions
Dong-Hwan Lee
Behrad Moniri
Xinmeng Huang
Yan Sun
Hamed Hassani
23
8
0
31 Jan 2023
Avoiding spurious correlations via logit correction
Avoiding spurious correlations via logit correction
Sheng Liu
Xu Zhang
Nitesh Sekhar
Yue Wu
Prateek Singhal
C. Fernandez‐Granda
30
29
0
02 Dec 2022
AGRO: Adversarial Discovery of Error-prone groups for Robust
  Optimization
AGRO: Adversarial Discovery of Error-prone groups for Robust Optimization
Bhargavi Paranjape
Pradeep Dasigi
Vivek Srikumar
Luke Zettlemoyer
Hannaneh Hajishirzi
36
7
0
02 Dec 2022
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers
Wanqian Yang
Polina Kirichenko
Micah Goldblum
A. Wilson
DRL
30
10
0
28 Nov 2022
Deep Learning-Based Prediction of Molecular Tumor Biomarkers from H&E: A
  Practical Review
Deep Learning-Based Prediction of Molecular Tumor Biomarkers from H&E: A Practical Review
Heather D. Couture
50
20
0
27 Nov 2022
DC-Check: A Data-Centric AI checklist to guide the development of
  reliable machine learning systems
DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems
Nabeel Seedat
F. Imrie
M. Schaar
32
12
0
09 Nov 2022
Detecting Shortcuts in Medical Images -- A Case Study in Chest X-rays
Detecting Shortcuts in Medical Images -- A Case Study in Chest X-rays
Amelia Jiménez-Sánchez
Dovile Juodelye
B. Chamberlain
V. Cheplygina
10
14
0
08 Nov 2022
On Feature Learning in the Presence of Spurious Correlations
On Feature Learning in the Presence of Spurious Correlations
Pavel Izmailov
Polina Kirichenko
Nate Gruver
A. Wilson
38
118
0
20 Oct 2022
Outlier-Robust Group Inference via Gradient Space Clustering
Outlier-Robust Group Inference via Gradient Space Clustering
Yuchen Zeng
Kristjan Greenewald
Kangwook Lee
Justin Solomon
Mikhail Yurochkin
41
2
0
13 Oct 2022
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training
  Dynamics
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics
Shoaib Ahmed Siddiqui
Nitarshan Rajkumar
Tegan Maharaj
David M. Krueger
Sara Hooker
47
27
0
20 Sep 2022
Detection of Malicious Websites Using Machine Learning Techniques
Detection of Malicious Websites Using Machine Learning Techniques
Adebayo Oshingbesan
Courage Ekoh
C. Okobi
A. Munezero
Richard Kagame
25
5
0
13 Sep 2022
Risk of Bias in Chest Radiography Deep Learning Foundation Models
Risk of Bias in Chest Radiography Deep Learning Foundation Models
Ben Glocker
Charles Jones
Mélanie Roschewitz
S. Winzeck
26
35
0
07 Sep 2022
Robustness of an Artificial Intelligence Solution for Diagnosis of
  Normal Chest X-Rays
Robustness of an Artificial Intelligence Solution for Diagnosis of Normal Chest X-Rays
T. Dyer
Jordan Smith
G. Dissez
N. Tay
Q. Malik
T. N. Morgan
P. Williams
Liliana Garcia-Mondragon
George Pearse
S. Rasalingham
OOD
19
2
0
31 Aug 2022
Subclass Knowledge Distillation with Known Subclass Labels
Subclass Knowledge Distillation with Known Subclass Labels
A. Sajedi
Y. Lawryshyn
Konstantinos N. Plataniotis
19
3
0
17 Jul 2022
Contrastive Adapters for Foundation Model Group Robustness
Contrastive Adapters for Foundation Model Group Robustness
Michael Zhang
Christopher Ré
VLM
23
62
0
14 Jul 2022
Towards a More Rigorous Science of Blindspot Discovery in Image
  Classification Models
Towards a More Rigorous Science of Blindspot Discovery in Image Classification Models
Gregory Plumb
Nari Johnson
Ángel Alexander Cabrera
Ameet Talwalkar
42
5
0
08 Jul 2022
Identifying the Context Shift between Test Benchmarks and Production
  Data
Identifying the Context Shift between Test Benchmarks and Production Data
Matthew Groh
OOD
21
8
0
03 Jul 2022
The Fallacy of AI Functionality
The Fallacy of AI Functionality
Inioluwa Deborah Raji
Indra Elizabeth Kumar
Aaron Horowitz
Andrew D. Selbst
34
180
0
20 Jun 2022
Modeling the Machine Learning Multiverse
Modeling the Machine Learning Multiverse
Samuel J. Bell
Onno P. Kampman
Jesse Dodge
Neil D. Lawrence
23
17
0
13 Jun 2022
Metrics reloaded: Recommendations for image analysis validation
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein
Annika Reinke
Patrick Godau
M. Tizabi
Florian Buettner
...
Aleksei Tiulpin
Sotirios A. Tsaftaris
Ben Van Calster
Gaël Varoquaux
Paul F. Jäger
34
218
0
03 Jun 2022
LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning
  Using a Lazy Influence Approximation
LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation
Ljubomir Rokvic
Panayiotis Danassis
Sai Praneeth Karimireddy
Boi Faltings
TDI
27
1
0
23 May 2022
Recommendations on test datasets for evaluating AI solutions in
  pathology
Recommendations on test datasets for evaluating AI solutions in pathology
A. Homeyer
Christian Geißler
L. O. Schwen
Falk Zakrzewski
Theodore Evans
...
Tobias Lang
P. Boor
Heimo Muller
P. Hufnagl
N. Zerbe
51
42
0
21 Apr 2022
Improved Group Robustness via Classifier Retraining on Independent
  Splits
Improved Group Robustness via Classifier Retraining on Independent Splits
Thien Hai Nguyen
Hongyang R. Zhang
Huy Le Nguyen
OOD
31
2
0
20 Apr 2022
Perfectly Balanced: Improving Transfer and Robustness of Supervised
  Contrastive Learning
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning
Mayee F. Chen
Daniel Y. Fu
A. Narayan
Michael Zhang
Zhao Song
Kayvon Fatahalian
Christopher Ré
SSL
32
48
0
15 Apr 2022
Rethinking Machine Learning Model Evaluation in Pathology
Rethinking Machine Learning Model Evaluation in Pathology
Syed Ashar Javed
Dinkar Juyal
Zahil Shanis
S. Chakraborty
Harsha Pokkalla
Aaditya (Adi) Prakash
LM&MA
33
12
0
11 Apr 2022
A Dempster-Shafer approach to trustworthy AI with application to fetal
  brain MRI segmentation
A Dempster-Shafer approach to trustworthy AI with application to fetal brain MRI segmentation
Lucas Fidon
Michael Aertsen
Florian Kofler
A. Bink
A. David
...
Marlene Stuempflen
Esther Van Elslander
Sébastien Ourselin
Jan Deprest
Tom Kamiel Magda Vercauteren
31
16
0
05 Apr 2022
Domino: Discovering Systematic Errors with Cross-Modal Embeddings
Domino: Discovering Systematic Errors with Cross-Modal Embeddings
Sabri Eyuboglu
M. Varma
Khaled Kamal Saab
Jean-Benoit Delbrouck
Christopher Lee-Messer
Jared A. Dunnmon
James Zou
Christopher Ré
38
143
0
24 Mar 2022
Distributionally Robust Optimization via Ball Oracle Acceleration
Distributionally Robust Optimization via Ball Oracle Acceleration
Y. Carmon
Danielle Hausler
18
12
0
24 Mar 2022
Pseudo Bias-Balanced Learning for Debiased Chest X-ray Classification
Pseudo Bias-Balanced Learning for Debiased Chest X-ray Classification
Luyang Luo
Dunyuan Xu
Hao Chen
T. Wong
Pheng-Ann Heng
CML
OOD
17
22
0
18 Mar 2022
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