No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning
for Medical Imaging

No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging

31 July 2023

Daniel Coelho De Castro

Fabio De Sousa Ribeiro

Melissa McCradden

Papers citing "No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging"

9 / 9 papers shown

Title
Bias Assessment and Data Drift Detection in Medical Image Analysis: A Survey Andrea Prenner Bernhard Kainz 26 0 0 26 Sep 2024
Semi-Supervised Learning for Deep Causal Generative Models Yasin Ibrahim Hermione Warr Konstantinos Kamnitsas OOD MedIm CML GAN 16 1 0 27 Mar 2024
RadEdit: stress-testing biomedical vision models via diffusion image editing Fernando Pérez-García Sam Bond-Taylor Pedro P. Sanchez B. V. Breugel Daniel Coelho De Castro ... M. Lungren A. Nori Javier Alvarez-Valle Ozan Oktay Maximilian Ilse MedIm 30 6 0 20 Dec 2023
A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records L. Guo Jason Alan Fries E. Steinberg Scott L. Fleming Keith Morse Catherine Aftandilian J. Posada Nigam Shah L. Sung OOD 6 12 0 20 Nov 2023
MOTOR: A Time-To-Event Foundation Model For Structured Medical Records E. Steinberg Jason Alan Fries Yizhe Xu N. Shah OOD AI4TS 15 13 0 09 Jan 2023
MEDFAIR: Benchmarking Fairness for Medical Imaging Yongshuo Zong Yongxin Yang Timothy M. Hospedales OOD 71 56 0 04 Oct 2022
Invariant and Transportable Representations for Anti-Causal Domain Shifts Yibo Jiang Victor Veitch OOD 118 32 0 04 Jul 2022
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings Jessica Schrouff Natalie Harris Oluwasanmi Koyejo Ibrahim M. Alabdulmohsin Eva Schnider ... Vivek Natarajan Alan Karthikesalingam Katherine A. Heller Silvia Chiappa Alexander DÁmour OOD 51 53 0 02 Feb 2022
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 208 663 0 17 Feb 2018