Evidence mapPaperPMID 42513667Full record

ArticleJournal of clinical medicine2026

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

Jaewon Jang, Yong Jun Choi, Taeyong Sim, Ki-Byung Lee, Ji-Hyun Kim, Eun Young Cho, Yuhyun Choi, Sungsoo Hong, Bo Mi Jung, Soo-Jeong Kim and 2 more

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Jaewon JangAITRICS Corp, Seoul 06221, Republic of Korea.
Yong Jun ChoiDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 04763, Republic of Korea.ORCID 0000-0002-6114-2059
Taeyong SimAITRICS Corp, Seoul 06221, Republic of Korea.
Ki-Byung LeeDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Chuncheon Sacred Heart Hospital, Hallym University Medical Center, Chuncheon 24253, Republic of Korea.ORCID 0000-0001-9106-5528
Ji-Hyun KimAITRICS Corp, Seoul 06221, Republic of Korea.ORCID 0000-0003-2701-4317
Eun Young ChoAITRICS Corp, Seoul 06221, Republic of Korea.ORCID 0000-0002-4778-1276
Yuhyun ChoiAITRICS Corp, Seoul 06221, Republic of Korea.
Sungsoo HongAITRICS Corp, Seoul 06221, Republic of Korea.ORCID 0000-0002-4534-9375
Bo Mi JungDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 04763, Republic of Korea.
Soo-Jeong KimDepartment of Internal Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin 16995, Republic of Korea.
Won Gi HongDepartment of Hospital Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin 16995, Republic of Korea.ORCID 0009-0007-2673-0844
Jae Hwa ChoDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 04763, Republic of Korea.ORCID 0000-0002-3432-3997

Funding

Korea Health Industry Development Institute HI22C1580
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

clinical decision support systemclinical deteriorationdeep learningearly predictionin-hospital adverse events

Identifiers

PMID42513667
PMCPMC13413000

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.