Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning

1 August 2022

Papers citing "Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning"

12 / 12 papers shown

Title
To which reference class do you belong? Measuring racial fairness of reference classes with normative modeling S. Rutherford T. Wolfers Charlotte J. Fraza Nathaniel G. Harrnet Christian F. Beckmann H. Ruhé A. Marquand CML 85 3 0 26 Jul 2024
Fair Classification with Group-Dependent Label Noise Jialu Wang Yang Liu Caleb C. Levy NoLa 44 103 0 31 Oct 2020
Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts Sarah Jabbour David Fouhey Ella Kazerooni Michael Sjoding Jenna Wiens OOD 47 49 0 21 Sep 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 209 2,052 0 16 Apr 2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible Antonin Berthon Bo Han Gang Niu Tongliang Liu Masashi Sugiyama NoLa 98 108 0 11 Jan 2020
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric Nathan Kallus Angela Zhou 88 74 0 15 Feb 2019
Identifying and Correcting Label Bias in Machine Learning Heinrich Jiang Ofir Nachum FaML 90 283 0 15 Jan 2019
Learning from positive and unlabeled data: a survey Jessa Bekker Jesse Davis 78 560 0 12 Nov 2018
Learning with Bounded Instance- and Label-dependent Label Noise Jiacheng Cheng Tongliang Liu K. Ramamohanarao Dacheng Tao NoLa 67 148 0 12 Sep 2017
Joint Distribution Optimal Transportation for Domain Adaptation Nicolas Courty Rémi Flamary Amaury Habrard A. Rakotomamonjy OT OOD 88 564 0 24 May 2017
Fast Threshold Tests for Detecting Discrimination Emma Pierson S. Corbett-Davies Sharad Goel 53 50 0 27 Feb 2017
Frustratingly Easy Domain Adaptation Hal Daumé 120 1,800 0 10 Jul 2009