An artificial intelligence system to predict the optimal timing for mechanical ventilation weaning for intensive care unit patients: A two-stage prediction approach.

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Title: An artificial intelligence system to predict the optimal timing for mechanical ventilation weaning for intensive care unit patients: A two-stage prediction approach.
Authors: Liu CF; Department of Medical Research, Chi Mei Medical Center, Tainan, Taiwan., Hung CM; Department of General Surgery, E-Da Cancer Hospital, Kaohsiung, Taiwan.; College of Medicine, I-Shou University, Kaohsiung, Taiwan., Ko SC; Department of Respiratory Therapy, Chi Mei Medical Center, Tainan, Taiwan., Cheng KC; Department of Internal Medicine, Chi Mei Medical Center, Tainan, Taiwan., Chao CM; Department of Intensive Care Medicine, Chi Mei Medical Center, Liouying, Taiwan.; Department of Dental Laboratory Technology, Min-Hwei College of Health Care Management, Liouying, Taiwan., Sung MI; Department of Respiratory Therapy, Chi Mei Medical Center, Tainan, Taiwan., Hsing SC; Department of Respiratory Therapy, Chi Mei Medical Center, Tainan, Taiwan., Wang JJ; Department of Anesthesiology, Chi Mei Medical Center, Tainan, Taiwan.; Department of Anesthesiology, National Defense Medical Center, Taipei, Taiwan., Chen CJ; Department of Information Systems, Chi Mei Medical Center, Tainan, Taiwan., Lai CC; Division of Hospital Medicine, Department of Internal Medicine, Chi Mei Medical Center, Tainan, Taiwan., Chen CM; Department of Intensive Care Medicine, Chi Mei Medical Center, Tainan, Taiwan., Chiu CC; Department of General Surgery, E-Da Cancer Hospital, Kaohsiung, Taiwan.; School of Medicine, College of Medicine, I-Shou University, Kaohsiung, Taiwan.; Department of Medical Education and Research, E-Da Cancer Hospital, Kaohsiung, Taiwan.; Department of General Surgery, Chi Mei Medical Center, Tainan, Taiwan.
Source: Frontiers in medicine [Front Med (Lausanne)] 2022 Nov 18; Vol. 9, pp. 935366. Date of Electronic Publication: 2022 Nov 18 (Print Publication: 2022).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101648047 Publication Model: eCollection Cited Medium: Print ISSN: 2296-858X (Print) Linking ISSN: 2296858X NLM ISO Abbreviation: Front Med (Lausanne) Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2296-858X
DOI:10.3389/fmed.2022.935366