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Clinical machine learning is increasingly multimodal, collected in both structured tabular formats and unstructured forms such as freetext.
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Swaraj Khadanga, Karan Aggarwal, Shafiq Joty, and Jaideep Srivastava. 2019 · 1909
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Equity and equality in health and health care
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Race bias, social class bias, and gender bias in clinical judgment
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, Eric Price, and Nati Srebro. 2016 · 2016
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MIMIC-III, a freely accessible critical care database
Alistair Johnson, Tom Pollard, Lu Shen, Li-wei Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Celi, and Roger Mark. 2016 · 2016
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Allennlp: A deep semantic natural language processing platform
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Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning
Steven Horng, David A Sontag, Yoni Halpern, Yacine Jernite, Nathan I Shapiro, and Larry A Nathanson. 2017 · 2017
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Why is my classifier discriminatory?
Irene Chen, Fredrik D Johansson, and David Sontag. 2018 · 2018
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Can AI Help Reduce Disparities in General Medical and Mental Health Care?
I. Y. Chen, P. Szolovits, and M. Ghassemi. 2019 · 2019
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Lipstick on a pig: Debiasing methods cover up systematic gender biases in word embeddings but do not remove them
Hila Gonen and Yoav Goldberg. 2019 · 2019
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Multitask learning and benchmarking with clinical time series data
Hrayr Harutyunyan, Hrant Khachatrian, David C. Kale, Greg Ver Steeg, and Aram Galstyan. 2019 · 2019
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A survey of word embeddings for clinical text
Faiza Khan Khattak, Serena Jeblee, Chloé Pou-Prom, Mohamed Abdalla, Christopher Meaney, and Frank Rudzicz. 2019 · 2019
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Black is to criminal as caucasian is to police: Detecting and removing multiclass bias in word embeddings
Thomas Manzini, Lim Yao Chong, Alan W Black, and Yulia Tsvetkov. 2019 · 2019
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Maya R. Gupta, Andrew Cotter, Mahdi Milani Fard, and Serena Wang. 2018 · 2018
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The cost of fairness in binary classification
Aditya Krishna Menon and Robert C Williamson. 2018 · 2018
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Ensuring fairness in machine learning to advance health equity
Alvin Rajkomar, Michaela Hardt, Michael D. Howell, Greg Corrado, and Marshall H. Chin. 2018 · 2018
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Learning gender-neutral word embeddings
Jieyu Zhao, Yichao Zhou, Zeyu Li, Wei Wang, and Kai-Wei Chang. 2018 · 2018
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Unstructured text in EMR improves prediction of death after surgery in children
Oguz Akbilgic, Ramin Homayouni, Kevin Heinrich, Max Raymond Langham, and Robert Lowell Davis. 2019 · 2019
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Counterfactual reasoning for fair clinical risk prediction
Stephen R. Pfohl, Tony Duan, Daisy Yi Ding, and Nigam H. Shah. 2019b
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Creating fair models of atherosclerotic cardiovascular disease risk
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What’s in a name? reducing bias in bios without access to protected attributes
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Biowordvec, improving biomedical word embeddings with subword information and mesh
Yijia Zhang, Qingyu Chen, Zhihao Yang, Hongfei Lin, and Zhiyong Lu. 2019 · 2019
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Designing fairly fair classifiers via economic fairness notions
Safwan Hossain, Andjela Mladenovic, and Nisarg Shah. 2020 · 2020
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Hurtful words: Quantifying biases in clinical contextual word embeddings
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