Fairness in TabNet Model by Disentangled Representation for the Prediction of Hospital No-Show

Flexibly fair representation learning by disentanglement

Original

Creager, E., Madras, D., Jacobsen, J.-H., Weis, M. A., Swersky, K., Pitassi, T., and Zemel, R. (2019) · 1906

Earlier work this paper cites.

Tabnet: Attentive interpretable tabular learning

Original

Arik, S. O. and Pfister, T. (2019) · 1908

Earlier work this paper cites.

Fairness by learning orthogonal disentangled representations

Original

Sarhan, M. H., Navab, N., Eslami, A., and Albarqouni, S. (2020) · 2003

Earlier work this paper cites.

Prevalence, predictors and economic consequences of no-shows

Kheirkhah, P., Feng, Q., Travis, L. M., Tavakoli-Tabasi, S., and Sharafkhaneh, A. (2015) · 2015

Earlier work this paper cites.

The variational fair autoencoder

Original

Louizos, C., Swersky, K., Li, Y., Welling, M., and Zemel, R. (2015) · 2015

Earlier work this paper cites.

Domain separation networks

Bousmalis, K., Trigeorgis, G., Silberman, N., Krishnan, D., and Erhan, D. (2016) · 2016

Cited alongside, same era.

Missed appointments cost the us healthcare system $150 b each year

Gier, J. (2017) · 2017

Cited alongside, same era.

Learning adversarially fair and transferable representations

Original

Madras, D., Creager, E., Pitassi, T., and Zemel, R. (2018) · 2018

Cited alongside, same era.

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Cited alongside, same era.

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Locatello, F., Abbati, G., Rainforth, T., Bauer, S., Schölkopf, B., and Bachem, O. (2019) · 2019

Later among the works it cites.

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Later among the works it cites.

Patient no-show prediction: A systematic literature review

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Later among the works it cites.

Individualized no-show predictions: Effect on clinic overbooking and appointment reminders

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