Systematic auditing is essential to debiasing machine learning in biology

Fatma-Elzahraa Eid et al. illustrate a principled approach for identifying biases that can inflate the performance of biological machine learning models. When applied to three biomedical prediction problems, they identify previously unrecognized biases and ultimately show that models are likely to l...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Fatma-Elzahraa Eid, Haitham A. Elmarakeby, Yujia Alina Chan, Nadine Fornelos, Mahmoud ElHefnawi, Eliezer M. Van Allen, Lenwood S. Heath, Kasper Lage
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/99b8c372383a4995a2577d5c731b5219
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:99b8c372383a4995a2577d5c731b5219
record_format	dspace
spelling	oai:doaj.org-article:99b8c372383a4995a2577d5c731b52192021-12-02T13:30:21ZSystematic auditing is essential to debiasing machine learning in biology10.1038/s42003-021-01674-52399-3642https://doaj.org/article/99b8c372383a4995a2577d5c731b52192021-02-01T00:00:00Zhttps://doi.org/10.1038/s42003-021-01674-5https://doaj.org/toc/2399-3642Fatma-Elzahraa Eid et al. illustrate a principled approach for identifying biases that can inflate the performance of biological machine learning models. When applied to three biomedical prediction problems, they identify previously unrecognized biases and ultimately show that models are likely to learn primarily from data biases when there is insufficient learnable signal in the data.Fatma-Elzahraa EidHaitham A. ElmarakebyYujia Alina ChanNadine FornelosMahmoud ElHefnawiEliezer M. Van AllenLenwood S. HeathKasper LageNature PortfolioarticleBiology (General)QH301-705.5ENCommunications Biology, Vol 4, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Fatma-Elzahraa Eid Haitham A. Elmarakeby Yujia Alina Chan Nadine Fornelos Mahmoud ElHefnawi Eliezer M. Van Allen Lenwood S. Heath Kasper Lage Systematic auditing is essential to debiasing machine learning in biology
description	Fatma-Elzahraa Eid et al. illustrate a principled approach for identifying biases that can inflate the performance of biological machine learning models. When applied to three biomedical prediction problems, they identify previously unrecognized biases and ultimately show that models are likely to learn primarily from data biases when there is insufficient learnable signal in the data.
format	article
author	Fatma-Elzahraa Eid Haitham A. Elmarakeby Yujia Alina Chan Nadine Fornelos Mahmoud ElHefnawi Eliezer M. Van Allen Lenwood S. Heath Kasper Lage
author_facet	Fatma-Elzahraa Eid Haitham A. Elmarakeby Yujia Alina Chan Nadine Fornelos Mahmoud ElHefnawi Eliezer M. Van Allen Lenwood S. Heath Kasper Lage
author_sort	Fatma-Elzahraa Eid
title	Systematic auditing is essential to debiasing machine learning in biology
title_short	Systematic auditing is essential to debiasing machine learning in biology
title_full	Systematic auditing is essential to debiasing machine learning in biology
title_fullStr	Systematic auditing is essential to debiasing machine learning in biology
title_full_unstemmed	Systematic auditing is essential to debiasing machine learning in biology
title_sort	systematic auditing is essential to debiasing machine learning in biology
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/99b8c372383a4995a2577d5c731b5219
work_keys_str_mv	AT fatmaelzahraaeid systematicauditingisessentialtodebiasingmachinelearninginbiology AT haithamaelmarakeby systematicauditingisessentialtodebiasingmachinelearninginbiology AT yujiaalinachan systematicauditingisessentialtodebiasingmachinelearninginbiology AT nadinefornelos systematicauditingisessentialtodebiasingmachinelearninginbiology AT mahmoudelhefnawi systematicauditingisessentialtodebiasingmachinelearninginbiology AT eliezermvanallen systematicauditingisessentialtodebiasingmachinelearninginbiology AT lenwoodsheath systematicauditingisessentialtodebiasingmachinelearninginbiology AT kasperlage systematicauditingisessentialtodebiasingmachinelearninginbiology
_version_	1718392929455702016

Systematic auditing is essential to debiasing machine learning in biology

Ejemplares similares