Fetching the paper…
Reading the bibliography…
ML-based predictions are used to inform consequential decisions about individuals.
Multicalibration: Calibration for the (Computationally-identifiable) masses
Hébert-Johnson, U., Kim, M. P., Reingold, O., and Rothblum, G. N. (2018) · 1948
Earlier work this paper cites.
Therapeutic decision making: a cost-benefit analysis
Pauker, S. G. and Kassirer, J. P. (1975) · 1975
Earlier work this paper cites.
On criteria for evaluating models of absolute risk
Gail, M. H. and Pfeiffer, R. M. (2005) · 2005
Earlier work this paper cites.
Decision curve analysis: a novel method for evaluating prediction models
Vickers, A. J. and Elkin, E. B. (2006) · 2006
Earlier work this paper cites.
Transferable calibration with lower bias and variance in domain adaptation
Wang, X., Long, M., Wang, J., and Jordan, M. I. (2020) · 2007
Earlier work this paper cites.
Clinical prediction models: a practical approach to development, validation, and updating: by ewout w. steyerberg
Alonzo, T. A. (2009) · 2009
Earlier work this paper cites.
Using relative utility curves to evaluate risk prediction
Baker, S. G., Cook, N. R., Vickers, A., and Kramer, B. S. (2009) · 2009
Earlier work this paper cites.
Predicting the 10 year risk of cardiovascular disease in the united kingdom: independent and external validation of an updated version of qrisk2
Collins, G. S. and Altman, D. G. (2012) · 2012
Earlier work this paper cites.
Beyond the usual prediction accuracy metrics: reporting results for clinical decision making
Localio, A. R. and Goodman, S. (2012) · 2012
Earlier work this paper cites.
Interpreting diagnostic accuracy studies for patient care
Mallett, S., Halligan, S., Thompson, M., Collins, G. S., and Altman, D. G. (2012) · 2012
Earlier work this paper cites.
Quantifying the added value of a diagnostic test or marker
Moons, K. G., de Groot, J. A., Linnet, K., Reitsma, J. B., and Bossuyt, P. M. (2012) · 2012
Earlier work this paper cites.
Calibration of clinical prediction rules does not just assess bias
Vach, W. (2013) · 2013
Cited alongside, same era.
Evaluation of markers and risk prediction models: overview of relationships between nri and decision-analytic measures
Van Calster, B., Vickers, A. J., Pencina, M. J., Baker, S. G., Timmerman, D., and Steyerberg, E. W. (2013) · 2013
Cited alongside, same era.
Net reclassification indices for evaluating risk-prediction instruments: a critical review
Kerr, K. F., Wang, Z., Janes, H., McClelland, R. L., Psaty, B. M., and Pepe, M. S. (2014) · 2014
Cited alongside, same era.
Obtaining well calibrated probabilities using bayesian binning
Naeini, M. P., Cooper, G., and Hauskrecht, M. (2015) · 2015
Cited alongside, same era.
Optimal decision-theoretic classification using non-decomposable performance metrics
Natarajan, N., Koyejo, O., Ravikumar, P., and Dhillon, I. S. (2015) · 2015
Cited alongside, same era.
Learning from outcomes: Evidence-based rankings
Dwork, C., Kim, M. P., Reingold, O., Rothblum, G. N., and Yona, G. (2019) · 2019
Later among the works it cites.
Multiaccuracy: Black-box post-processing for fairness in classification
Kim, M. P., Ghorbani, A., and Zou, J. (2019) · 2019
Later among the works it cites.
A simple, step-by-step guide to interpreting decision curve analysis
Vickers, A. J., van Calster, B., and Steyerberg, E. W. (2019) · 2019
Later among the works it cites.
Addressing bias in prediction models by improving subpopulation calibration
Barda, N., Yona, G., Rothblum, G. N., Greenland, P., Leibowitz, M., Balicer, R., Bachmat, E., and Dagan, N. (2021) · 2021
Later among the works it cites.
Outcome indistinguishability
Dwork, C., Kim, M. P., Reingold, O., Rothblum, G. N., and Yona, G. (2021) · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Calibration of risk prediction models: impact on decision-analytic performance
Van Calster, B. and Vickers, A. J. (2015) · 2015
Cited alongside, same era.
Assessing the clinical impact of risk prediction models with decision curves: guidance for correct interpretation and appropriate use
Kerr, K. F., Brown, M. D., Zhu, K., and Janes, H. (2016) · 2016
Cited alongside, same era.
A calibration hierarchy for risk models was defined: from utopia to empirical data
Van Calster, B., Nieboer, D., Vergouwe, Y., De Cock, B., Pencina, M. J., and Steyerberg, E. W. (2016) · 2016
Cited alongside, same era.
Algorithmic decision making and the cost of fairness
Corbett-Davies, S., Pierson, E., Feller, A., Goel, S., and Huq, A. (2017) · 2017
Cited alongside, same era.
Consistency analysis for binary classification revisited
Dembczyński, K., Kotłowski, W., Koyejo, O., and Natarajan, N. (2017) · 2017
Cited alongside, same era.
From soft classifiers to hard decisions: How fair can we be?
Canetti, R., Cohen, A., Dikkala, N., Ramnarayan, G., Scheffler, S., and Smith, A. (2019) · 2019
Cited alongside, same era.
Pfohl, S. R., Xu, Y., Foryciarz, A., Ignatiadis, N., Genkins, J., and Shah, N. H. (2022a)
Cited in the paper.
Gopalan, P., Kalai, A. T., Reingold, O., Sharan, V., and Wieder, U. (2021) · 2021
Later among the works it cites.
Online multivalid learning: Means, moments, and prediction intervals
Gupta, V., Jung, C., Noarov, G., Pai, M. M., and Roth, A. (2021) · 2021
Later among the works it cites.
Moment multicalibration for uncertainty estimation
Jung, C., Lee, C., Pai, M., Roth, A., and Vohra, R. (2021) · 2021
Later among the works it cites.
Multi-group agnostic pac learnability
Rothblum, G. N. and Yona, G. (2021) · 2021
Later among the works it cites.
On calibration and out-of-domain generalization
Wald, Y., Feder, A., Greenfeld, D., and Shalit, U. (2021) · 2021
Later among the works it cites.
Development and validation of models to predict pathological outcomes of radical prostatectomy in regional and national cohorts
Ötleş, E., Denton, B. T., Qu, B., Murali, A., Merdan, S., Auffenberg, G. B., Hiller, S. C., Lane, B. R., George, A. K., and Singh, K. (2022) · 2022
Closest in time.