Evidence map›Paper›PMID 42713780›Full record

ArticleCritical care explorations2026

Building Clinical Artificial Intelligence at the PICU Bedside: Recognizing the Clinician-Builder.

David Gilad, Abraham Tsur, Reut Kassif Lerner

Abstract read
In one paragraph

Article in Critical care explorations, 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

3 authors.

David GiladDepartment of Pediatric Intensive Care, Edmond and Lily Safra Children's Hospital, Sheba Medical Center, Ramat Gan, Israel.ORCID 0009-0004-5825-8968
Abraham TsurSheba ARC AI Center, Chaim Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel.
Reut Kassif LernerDepartment of Pediatric Intensive Care, Edmond and Lily Safra Children's Hospital, Sheba Medical Center, Ramat Gan, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several of the highest-value problems in critical care-synthesizing fragmented bedside data, surfacing the tacit heuristics of experienced clinicians, generating accurate family-facing explanations, and decision support-are too specialized, too local, and too embedded in uncodified practice to specify from outside the unit; the market they represent is often too small to repay commercial development. This commentary argues for recognizing a missing translational figure: the clinician-builder-a frontline clinician who identifies workflow failures and prototypes tools to address them, much as the clinician-scientist did for molecular medicine. Because a prototype is not a product, the clinician-builder co-develops intended use, evidence, and governance with institutional artificial intelligence (AI) centers. Pediatric intensive care should not be the last setting to receive clinical AI, but among the first where it is judged-and a blueprint for other specialties.

Indexed as

Artificial IntelligenceCritical CareIntensive Care Units, PediatricPoint-of-Care SystemsHumansWorkflowclinical artificial intelligenceclinical informaticsimplementation sciencepediatric critical carephysician-led innovationworkflow integration

Identifiers

PMID42713780
PMCPMC13557764

What Socratic holds

Textmetadata
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.