Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records

Hans-Christian Thorsen-Meyer; Annelaura B. Nielsen; Anna P. Nielsen; Benjamin Skov Kaas-Hansen; Palle Toft; Jens Schierbeck; Thomas Strøm; Piotr J. Chmura; Marc Heimann; Lars Dybdahl; Lasse Spangsege; Patrick Hulsen; Kirstine Belling; Søren Brunak; Anders Perner

doi:10.1016/S2589-7500(20)30018-2

Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records

Hans-Christian Thorsen-Meyer, Annelaura B. Nielsen, Anna P. Nielsen, Benjamin Skov Kaas-Hansen, Palle Toft, Jens Schierbeck, Thomas Strøm, Piotr J. Chmura, Marc Heimann, Lars Dybdahl, Lasse Spangsege, Patrick Hulsen, Kirstine Belling, Søren Brunak, Anders Perner

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

206 Citationer (Scopus)

95 Downloads (Pure)

Originalsprog	Engelsk
Tidsskrift	The Lancet Digital Health
Vol/bind	2
Udgave nummer	4
Sider (fra-til)	e179–91
Antal sider	13
DOI	https://doi.org/10.1016/S2589-7500(20)30018-2
Status	Udgivet - 2020

Adgang til dokumentet

10.1016/S2589-7500(20)30018-2Licens: CC BY

Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient recordsForlagets udgivne version, 4,2 MBLicens: CC BY

Citationsformater

Thorsen-Meyer, H.-C., Nielsen, A. B., Nielsen, A. P., Kaas-Hansen, B. S., Toft, P., Schierbeck, J., Strøm, T., Chmura, P. J., Heimann, M., Dybdahl, L., Spangsege, L., Hulsen, P., Belling, K., Brunak, S., & Perner, A. (2020). Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records. The Lancet Digital Health, 2(4), e179–91. https://doi.org/10.1016/S2589-7500(20)30018-2

Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records. / Thorsen-Meyer, Hans-Christian; Nielsen, Annelaura B.; Nielsen, Anna P. et al.
I: The Lancet Digital Health, Bind 2, Nr. 4, 2020, s. e179–91.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

Thorsen-Meyer, H-C, Nielsen, AB, Nielsen, AP, Kaas-Hansen, BS, Toft, P, Schierbeck, J, Strøm, T, Chmura, PJ, Heimann, M, Dybdahl, L, Spangsege, L, Hulsen, P, Belling, K, Brunak, S & Perner, A 2020, 'Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records', The Lancet Digital Health, bind 2, nr. 4, s. e179–91. https://doi.org/10.1016/S2589-7500(20)30018-2

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title = "Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records",

author = "Hans-Christian Thorsen-Meyer and Nielsen, {Annelaura B.} and Nielsen, {Anna P.} and Kaas-Hansen, {Benjamin Skov} and Palle Toft and Jens Schierbeck and Thomas Str{\o}m and Chmura, {Piotr J.} and Marc Heimann and Lars Dybdahl and Lasse Spangsege and Patrick Hulsen and Kirstine Belling and S{\o}ren Brunak and Anders Perner",

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T1 - Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records

AU - Thorsen-Meyer, Hans-Christian

AU - Nielsen, Annelaura B.

AU - Nielsen, Anna P.

AU - Kaas-Hansen, Benjamin Skov

AU - Toft, Palle

AU - Schierbeck, Jens

AU - Strøm, Thomas

AU - Chmura, Piotr J.

AU - Heimann, Marc

AU - Dybdahl, Lars

AU - Spangsege, Lasse

AU - Hulsen, Patrick

AU - Belling, Kirstine

AU - Brunak, Søren

AU - Perner, Anders

PY - 2020

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DO - 10.1016/S2589-7500(20)30018-2

M3 - Journal article

SN - 2589-7500

VL - 2

SP - e179–91

JO - The Lancet Digital Health

JF - The Lancet Digital Health

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