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Machine learning models are often personalized with categorical attributes that are protected, sensitive, self-reported, or costly to acquire.
What is fair use?
Leon R Yankwich · 1954
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Multiple comparisons among means
Olive Jean Dunn · 1961
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Elicitation of personal probabilities and expectations
Leonard J Savage · 1971
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Truthful disclosure of information
Boyan Jovanovic · 1982
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The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations
Reuben M Baron and David A Kenny · 1986
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International application of a new probability algorithm for the diagnosis of coronary artery disease
Robert Detrano, Andras Janosi, Walter Steinbrunn, Matthias Pfisterer, Johann-Jakob Schmid, Sarbjit Sandhu, Kern H Guppy, Stella Lee, and Victor Froelicher · 1989
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Projecting individualized probabilities of developing breast cancer for white females who are being examined annually
Mitchell H Gail, Louise A Brinton, David P Byar, Donald K Corle, Sylvan B Green, Catherine Schairer, and John J Mulvihill · 1989
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A new simplified acute physiology score (saps ii) based on a european/north american multicenter study
Jean-Roger Le Gall, Stanley Lemeshow, and Fabienne Saulnier · 1993
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Bootstrap confidence intervals
Thomas J DiCiccio and Bradley Efron · 1996
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Vaginal birth after cesarean delivery: an admission scoring system
Bruce L Flamm and Ann M Geiger · 1997
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Approximate statistical tests for comparing supervised classification learning algorithms
Thomas G Dietterich · 1998
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Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
John Platt et al · 1999
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The world health organization adult adhd self-report scale (asrs): a short screening scale for use in the general population
Ronald C Kessler, Lenard Adler, Minnie Ames, Olga Demler, Steve Faraone, EVA Hiripi, Mary J Howes, Robert Jin, Kristina Secnik, Thomas Spencer, et al · 2005
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What is personalization? perspectives on the design and implementation of personalization in information systems
Haiyan Fan and Marshall Scott Poole · 2006
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Strictly proper scoring rules, prediction, and estimation
Tilmann Gneiting and Adrian E Raftery · 2007
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Glucocorticoid-induced osteoporosis: a systematic review and cost-utility analysis
JA Kanis, M Stevenson, EV McCloskey, S Davis, and Myfanwy Lloyd-Jones · 2007
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Dataset shift in machine learning
Joaquin Quiñonero-Candela, Masashi Sugiyama, Anton Schwaighofer, and Neil D Lawrence · 2008
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A new equation to estimate glomerular filtration rate
Andrew S Levey, Lesley A Stevens, Christopher H Schmid, Yaping Zhang, Alejandro F Castro III, Harold I Feldman, John W Kusek, Paul Eggers, Frederick Van Lente, Tom Greene, et al · 2009
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A survey of cross-validation procedures for model selection
Sylvain Arlot and Alain Celisse · 2010
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The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online
Gaurav Bansal, David Gefen, et al · 2010
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Assessing the performance of prediction models: a framework for some traditional and novel measures
Ewout W Steyerberg, Andrew J Vickers, Nancy R Cook, Thomas Gerds, Mithat Gonen, Nancy Obuchowski, Michael J Pencina, and Michael W Kattan · 2010
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Making sense of fair use
Neil Weinstock Netanel · 2011
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Framework for the impact analysis and implementation of clinical prediction rules (cprs)
Emma Wallace, Susan M Smith, Rafael Perera-Salazar, Paul Vaucher, Colin McCowan, Gary Collins, Jan Verbakel, Monica Lakhanpaul, and Tom Fahey · 2011
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Reporting and methods in clinical prediction research: a systematic review
Walter Bouwmeester, Nicolaas PA Zuithoff, Susan Mallett, Mirjam I Geerlings, Yvonne Vergouwe, Ewout W Steyerberg, Douglas G Altman, and Karel GM Moons · 2012
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Derivation and validation of the denver human immunodeficiency virus (hiv) risk score for targeted hiv screening
Jason S Haukoos, Michael S Lyons, Christopher J Lindsell, Emily Hopkins, Brooke Bender, Richard E Rothman, Yu-Hsiang Hsieh, Lynsay A MacLaren, Mark W Thrun, Comilla Sasson, et al · 2012
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A lasso for hierarchical interactions
Jacob Bien, Jonathan Taylor, and Robert Tibshirani · 2013
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Diagnostic accuracy measures
Paolo Eusebi · 2013
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Derivation and validation of a clinical prediction rule for uncomplicated ureteral stone—the stone score: retrospective and prospective observational cohort studies
Christopher L Moore, Scott Bomann, Brock Daniels, Seth Luty, Annette Molinaro, Dinesh Singh, and Cary P Gross · 2014
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Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (tripod): the tripod statement
Gary S Collins, Johannes B Reitsma, Douglas G Altman, and Karel GM Moons · 2015
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Certifying and removing disparate impact
Michael Feldman, Sorelle A Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian · 2015
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Learning interactions via hierarchical group-lasso regularization
Michael Lim and Trevor Hastie · 2015
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Obtaining well calibrated probabilities using bayesian binning
Mahdi Pakdaman Naeini, Gregory Cooper, and Milos Hauskrecht · 2015
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Simplified acute physiology score ii as predictor of mortality in intensive care units: a decision curve analysis
Jérôme Allyn, Cyril Ferdynus, Michel Bohrer, Cécile Dalban, Dorothée Valance, and Nicolas Allou · 2016
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The critical importance of risk score calibration: time for transformative approach to risk score validation?, 2016
Michael J Blaha · 2016
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nati Srebro · 2016
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Multi-task learning for predicting health, stress, and happiness
N. Jaques, Taylor S. Taylor, Nosakhare E. Nosakhare, Sano A. Sano, and & Picard R. Picard R · 2016
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Michael P Kim, Aleksandra Korolova, Guy N Rothblum, and Gal Yona · 2019
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Fairness with minimal harm: A pareto-optimal approach for healthcare
Natalia Martinez, Martin Bertran, and Guillermo Sapiro · 2019
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Model cards for model reporting
Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru · 2019
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Creating fair models of atherosclerotic cardiovascular disease risk
Stephen Pfohl, Ben Marafino, Adrien Coulet, Fatima Rodriguez, Latha Palaniappan, and Nigam H Shah · 2019
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Learning optimized risk scores
Berk Ustun and Cynthia Rudin · 2019
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Alistair EW Johnson, Tom J Pollard, Lu Shen, H Lehman Li-Wei, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016
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Field synopsis of sex in clinical prediction models for cardiovascular disease
Jessica K Paulus, Benjamin S Wessler, Christine Lundquist, Lana LY Lai, Gowri Raman, Jennifer S Lutz, and David M Kent · 2016
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Supersparse Linear Integer Models for Optimized Medical Scoring Systems
Berk Ustun and Cynthia Rudin · 2016
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Clinical prediction models for sleep apnea: the importance of medical history over symptoms
Berk Ustun, M Brandon Westover, Cynthia Rudin, and Matt T Bianchi · 2016
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Now is the time for a postracial medicine: Biomedical research, the national institutes of health, and the perpetuation of scientific racism
Javier Perez-Rodriguez and Alejandro de la Fuente · 2017
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Personalized multitask learning for predicting tomorrow’s mood, stress, and health
Sara Taylor, Natasha Jaques, Ehimwenma Nosakhare, Akane Sano, and Rosalind Picard · 2017
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The world health organization adult attention-deficit/hyperactivity disorder self-report screening scale for dsm-5
Berk Ustun, Lenard A Adler, Cynthia Rudin, Stephen V Faraone, Thomas J Spencer, Patricia Berglund, Michael J Gruber, and Ronald C Kessler · 2017
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Fairness without harm: Decoupled classifiers with preference guarantees
Berk Ustun, Yang Liu, and David Parkes · 2019
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From predictive to prescriptive analytics
Dimitris Bertsimas and Nathan Kallus · 2020
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Model distillation for revenue optimization: Interpretable personalized pricing
Max Biggs, Wei Sun, and Markus Ettl · 2020
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Equal credit opportunity act
Federal Trade Commission · 2020
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The predictive approaches to treatment effect heterogeneity (path) statement
David M Kent, Jessica K Paulus, David Van Klaveren, Ralph D’Agostino, Steve Goodman, Rodney Hayward, John PA Ioannidis, Bray Patrick-Lake, Sally Morton, Michael Pencina, et al · 2020
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Minimax pareto fairness: A multi objective perspective
Natalia Martinez, Martin Bertran, and Guillermo Sapiro · 2020
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Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities
Jessica K Paulus and David M Kent · 2020
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Efficient interaction selection for clustered data via stagewise generalized estimating equations
Gregory Vaughan, Robert Aseltine, Kun Chen, and Jun Yan · 2020
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Davide Viviano and Jelena Bradic · 2020
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Hidden in plain sight—reconsidering the use of race correction in clinical algorithms, 2020
Darshali A Vyas, Leo G Eisenstein, and David S Jones · 2020
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Blastocyst score, a blastocyst quality ranking tool, is a predictor of blastocyst ploidy and implantation potential
Qiansheng Zhan, ET Sierra, Jonas Malmsten, Zhen Ye, Zev Rosenwaks, and Nikica Zaninovic · 2020
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Designing disaggregated evaluations of ai systems: Choices, considerations, and tradeoffs
Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, Duncan Wadsworth, and Hanna Wallach · 2021
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Disaggregated interventions to reduce inequality
Lucius Bynum, Joshua Loftus, and Julia Stoyanovich · 2021
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The need to separate the wheat from the chaff in medical informatics, 2021
Federico Cabitza and Andrea Campagner · 2021
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Online certification of preference-based fairness for personalized recommender systems
Virginie Do, Sam Corbett-Davies, Jamal Atif, and Nicolas Usunier · 2021
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The clinician and dataset shift in artificial intelligence
Samuel G Finlayson, Adarsh Subbaswamy, Karandeep Singh, John Bowers, Annabel Kupke, Jonathan Zittrain, Isaac S Kohane, and Suchi Saria · 2021
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Systematic review of approaches to preserve machine learning performance in the presence of temporal dataset shift in clinical medicine
Lin Lawrence Guo, Stephen R Pfohl, Jason Fries, Jose Posada, Scott Lanyon Fleming, Catherine Aftandilian, Nigam Shah, and Lillian Sung · 2021
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Learning optimal predictive checklists
Haoran Zhang, Quaid Morris, Berk Ustun, and Marzyeh Ghassemi · 2021
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Write it like you see it: Detectable differences in clinical notes by race lead to differential model recommendations
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Ai recognition of patient race in medical imaging: a modelling study
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An algorithmic framework for bias bounties
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On the epistemic limits of personalized prediction
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The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression
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Towards intersectionality in machine learning: Including more identities, handling underrepresentation, and performing evaluation
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Participatory systems for personalized prediction
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