Length of Stay Prediction With Standardized Hospital Data From Acute and Emergency Care Using a Deep Neural Network

*Research on Healthcare Performance RESHAPE, Inserm U1290, Université Claude Bernard Lyon 1, Lyon, France

†INSA Lyon, Université Lumière Lyon 2, Université Claude Bernard Lyon 1, Université Jean Monnet Saint-Etienne, DISP UR4570, Villeurbanne, France

‡Université Jean Monnet Saint-Etienne, INSA Lyon, Université Lumière Lyon 2, Université Claude Bernard Lyon 1, DISP UR4570, Roanne, France

§Mines Saint-Etienne, Univ. Clermont Auvergne, CNRS, CIS Center, Saint-Etienne, France

∥Department of Health Data, Lyon University Hospital, Lyon, France

This work is partially supported by the European Research Ambition Pack 2018 grant, distributed by the French Auvergne Rhône-Alpes region.

The authors declare no conflict of interest.

Correspondence to: Vincent Lequertier, PhD, 162 Avenue Lacassagne, Batiment A, 6ème étage, Lyon 69003, France. E-mail: [email protected].

Supplemental Digital Content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journal's website, www.lww-medicalcare.com.

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