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Determining a Clinically Applicable Cutoff in AI Algorithms for Predicting Clinical Deterioration: A Workload-Constrained, Alarm-Based Approach.

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Title: Determining a Clinically Applicable Cutoff in AI Algorithms for Predicting Clinical Deterioration: A Workload-Constrained, Alarm-Based Approach.
Authors: Jang J; AITRICS Corp, Seoul 06221, Republic of Korea., Choi YJ; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 04763, Republic of Korea., Sim T; AITRICS Corp, Seoul 06221, Republic of Korea.; AITRICS Inc., McLean, VA 22102, USA., Lee KB; Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Chuncheon Sacred Heart Hospital, Hallym University Medical Center, Chuncheon 24253, Republic of Korea., Kim JH; AITRICS Corp, Seoul 06221, Republic of Korea., Cho EY; AITRICS Corp, Seoul 06221, Republic of Korea., Choi Y; AITRICS Corp, Seoul 06221, Republic of Korea., Hong S; AITRICS Corp, Seoul 06221, Republic of Korea., Jung BM; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 04763, Republic of Korea., Kim SJ; Department of Internal Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin 16995, Republic of Korea., Hong WG; Department of Hospital Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin 16995, Republic of Korea., Cho JH; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 04763, Republic of Korea.
Source: Journal of clinical medicine [J Clin Med] 2026 Jul 22; Vol. 15 (14). Date of Electronic Publication: 2026 Jul 22.
Publication Type: Journal Article
Journal Info: Publisher: MDPI AG Country of Publication: Switzerland NLM ID: 101606588 Publication Model: Electronic Cited Medium: Print ISSN: 2077-0383 (Print) Linking ISSN: 20770383 NLM ISO Abbreviation: J Clin Med Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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ISSN:2077-0383
DOI:10.3390/jcm15145753