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MLHOps: Machine Learning for Healthcare Operations

MLHOps: Machine Learning for Healthcare Operations

4 May 2023
Kristoffer Larsen
Vallijah Subasri
A. Krishnan
Cláudio Tinoco Mesquita
Diana Paez
Laleh Seyyed-Kalantari
Amalia Peix
    LM&MA
    AI4TS
    VLM
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Papers citing "MLHOps: Machine Learning for Healthcare Operations"

25 / 75 papers shown
Title
Interpreting Adversarially Trained Convolutional Neural Networks
Interpreting Adversarially Trained Convolutional Neural Networks
Tianyuan Zhang
Zhanxing Zhu
AAML
GAN
FAtt
94
161
0
23 May 2019
Three scenarios for continual learning
Three scenarios for continual learning
Gido M. van de Ven
A. Tolias
CLL
94
891
0
15 Apr 2019
Publicly Available Clinical BERT Embeddings
Publicly Available Clinical BERT Embeddings
Emily Alsentzer
John R. Murphy
Willie Boag
W. Weng
Di Jin
Tristan Naumann
Matthew B. A. McDermott
AI4MH
145
1,971
0
06 Apr 2019
Bias in Bios: A Case Study of Semantic Representation Bias in a
  High-Stakes Setting
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
Maria De-Arteaga
Alexey Romanov
Hanna M. Wallach
J. Chayes
C. Borgs
Alexandra Chouldechova
S. Geyik
K. Kenthapadi
Adam Tauman Kalai
181
455
0
27 Jan 2019
MIMIC-CXR-JPG, a large publicly available database of labeled chest
  radiographs
MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs
Alistair E. W. Johnson
Tom Pollard
Nathaniel R. Greenbaum
M. Lungren
Chih-ying Deng
Yifan Peng
Zhiyong Lu
R. Mark
Seth Berkowitz
Steven Horng
MedIm
94
810
0
21 Jan 2019
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and
  Expert Comparison
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
Jeremy Irvin
Pranav Rajpurkar
M. Ko
Yifan Yu
Silviana Ciurea-Ilcus
...
D. Larson
C. Langlotz
Bhavik Patel
M. Lungren
A. Ng
112
2,594
0
21 Jan 2019
A review of domain adaptation without target labels
A review of domain adaptation without target labels
Wouter M. Kouw
Marco Loog
OOD
VLM
34
487
0
16 Jan 2019
Failing Loudly: An Empirical Study of Methods for Detecting Dataset
  Shift
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift
Stephan Rabanser
Stephan Günnemann
Zachary Chase Lipton
54
367
0
29 Oct 2018
Sanity Checks for Saliency Maps
Sanity Checks for Saliency Maps
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
FAtt
AAML
XAI
127
1,966
0
08 Oct 2018
Learning Gender-Neutral Word Embeddings
Learning Gender-Neutral Word Embeddings
Jieyu Zhao
Yichao Zhou
Zeyu Li
Wei Wang
Kai-Wei Chang
FaML
91
412
0
29 Aug 2018
Adversarial Removal of Demographic Attributes from Text Data
Adversarial Removal of Demographic Attributes from Text Data
Yanai Elazar
Yoav Goldberg
FaML
92
308
0
20 Aug 2018
Confounding variables can degrade generalization performance of
  radiological deep learning models
Confounding variables can degrade generalization performance of radiological deep learning models
J. Zech
Marcus A. Badgeley
Manway Liu
A. Costa
J. Titano
Eric K. Oermann
OOD
83
1,175
0
02 Jul 2018
Robustness May Be at Odds with Accuracy
Robustness May Be at Odds with Accuracy
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Alexander Turner
Aleksander Madry
AAML
99
1,778
0
30 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning
Exploiting Unintended Feature Leakage in Collaborative Learning
Luca Melis
Congzheng Song
Emiliano De Cristofaro
Vitaly Shmatikov
FedML
142
1,474
0
10 May 2018
Detecting and Correcting for Label Shift with Black Box Predictors
Detecting and Correcting for Label Shift with Black Box Predictors
Zachary Chase Lipton
Yu Wang
Alex Smola
OOD
60
553
0
12 Feb 2018
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep
  Learning
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
Pranav Rajpurkar
Jeremy Irvin
Kaylie Zhu
Brandon Yang
Hershel Mehta
...
Aarti Bagul
C. Langlotz
K. Shpanskaya
M. Lungren
A. Ng
LM&MA
78
2,702
0
14 Nov 2017
Automated Curriculum Learning for Neural Networks
Automated Curriculum Learning for Neural Networks
Alex Graves
Marc G. Bellemare
Jacob Menick
Rémi Munos
Koray Kavukcuoglu
74
523
0
10 Apr 2017
On the Reliable Detection of Concept Drift from Streaming Unlabeled Data
On the Reliable Detection of Concept Drift from Streaming Unlabeled Data
Tegjyot Singh Sethi
M. Kantardzic
33
177
0
31 Mar 2017
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
297
2,110
0
24 Oct 2016
Revisiting Classifier Two-Sample Tests
Revisiting Classifier Two-Sample Tests
David Lopez-Paz
Maxime Oquab
155
402
0
20 Oct 2016
Equality of Opportunity in Supervised Learning
Equality of Opportunity in Supervised Learning
Moritz Hardt
Eric Price
Nathan Srebro
FaML
222
4,307
0
07 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores
Inherent Trade-Offs in the Fair Determination of Risk Scores
Jon M. Kleinberg
S. Mullainathan
Manish Raghavan
FaML
114
1,769
0
19 Sep 2016
Recurrent Neural Networks for Multivariate Time Series with Missing
  Values
Recurrent Neural Networks for Multivariate Time Series with Missing Values
Zhengping Che
S. Purushotham
Kyunghyun Cho
David Sontag
Yan Liu
AI4TS
305
1,934
0
06 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
1.2K
16,954
0
16 Feb 2016
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
Nitesh Chawla
Kevin W. Bowyer
Lawrence Hall
W. Kegelmeyer
AI4TS
361
25,642
0
09 Jun 2011
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