An interpretable 1D convolutional neural network for detecting patient-ventilator asynchrony in mechanical ventilation

Pan, Q; Zhang, LW; Jia, MZ; Pan, J; Gong, Q; Lu, YF; Zhang, ZH; Ge, HQ; Fang, LP

Fang, LP (corresponding author), Zhejiang Univ Technol, Coll Informat Engn, Liuhe Rd 288, Hangzhou 310023, Peoples R China.; Ge, HQ (corresponding author), Zhejiang Univ, Sir Run Run Shaw Hosp, Natl Inst Resp Dis, Dept Resp Care,Reg Med Ctr,Sch Med, Qingchun East Rd 3, Hangzhou 310016, Peoples R China.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2021; 204 ():

Abstract

Background and Objective: Patient-ventilator asynchrony (PVA) is the result of a mismatch between the need of patients and the assistance provided by ......

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