Predicting weaning difficulty for planned extubation patients with an artificial neural network

doi:10.1097/MD.0000000000017392

CNU IR > College of Sustainable Environment and Recreation > Dept. of Recreation and Health-Care Management > Periodical Articles > Item 310902800/32512

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Title:	Predicting weaning difficulty for planned extubation patients with an artificial neural network
Authors:	Hsieh, Meng Hsuen Hsieh, Meng Ju Cheng, Ai-Chin Chen, Chin-Ming Hsieh, Chia-Chang Chao, Chien-Ming Lai, Chih-Cheng Cheng, Kuo-Chen Willy Chou(周偉倪)
Contributors:	Univ Calif Berkeley, Dept Elect Engn & Comp Sci Poznan Univ Med Sci, Dept Med Chang Jung Christian Univ, Dept Med Sci Ind Chi Mei Med Ctr, Dept Internal Med, Sect Resp Care Chi Mei Med Ctr, Dept Intens Care Med China Med Univ, Childrens Hosp Chi Mei Med Ctr, Dept Intens Care Med Kaohsiung Vet Gen Hosp, Dept Internal Med Chi Mei Med Ctr, Dept Phys Med & Rehabil Chia Nan Univ Pharm & Sci, Dept Recreat & Healthcare Management
Keywords:	artificial neural network planned extubation prediction weaning difficulty
Date:	2019-10
Issue Date:	2020-07-29 13:48:01 (UTC+8)
Publisher:	LIPPINCOTT WILLIAMS & WILKINS
Abstract:	This study aims to construct a neural network to predict weaning difficulty among planned extubation patients in intensive care units. This observational cohort study was conducted in eight adult ICUs in a medical center about adult patients experiencing planned extubation. The data of 3602 patients with planned extubation in ICUs of Chi-Mei Medical Center (from Dec. 2009 through Dec. 2011) was used to train and test an artificial neural network (ANN) model. The input features contain 47 clinical risk factors and the outputs are classified into three categories: simple, difficult, and prolonged weaning. A deep ANN model with four hidden layers of 30 neurons each was developed. The accuracy is 0.769 and the area under receiver operating characteristic curve for simple weaning, prolonged weaning, and difficult weaning are 0.910, 0.849, and 0.942 respectively. The results revealed that the ANN model achieved a good performance in prediction the weaning difficulty in planned extubation patients. Such a model will be helpful for predicting ICU patients' successful planned extubation.
Relation:	Medicine, v.98, n.40, e17392
Appears in Collections:	[Dept. of Recreation and Health-Care Management] Periodical Articles

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