A machine learning-enabled partially observable markov decision process framework for early sepsis prediction

Zeyu Liu, Anahita Khojandi, Xueping Li, Akram Mohammed, Robert L Davis, Rishikesan Kamaleswaran

Year of publication:	2022
Authors:	Liu, Zeyu ; Khojandi, Anahita ; Li, Xueping ; Mohammed, Akram ; Davis, Robert L. ; Kamaleswaran, Rishikesan
Published in:	INFORMS journal on computing : JOC ; charting new directions in operations research and computer science ; a journal of the Institute for Operations Research and the Management Sciences. - Linthicum, Md. : INFORMS, ISSN 1526-5528, ZDB-ID 2004082-9. - Vol. 34.2022, 4, p. 2039-2057
Subject:	hierarchical modeling \| medical decision making \| partially observable Markov decision processes \| real-time predictive analytics \| sepsis \| Entscheidung \| Decision \| Markov-Kette \| Markov chain \| Theorie \| Theory \| Prognoseverfahren \| Forecasting model

Type of publication:	Article
Type of publication (narrower categories):	Aufsatz in Zeitschrift ; Article in journal
Language:	English
Other identifiers:	10.1287/ijoc.2022.1176 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013362643