Evidence map›Paper›PMID 41963517›Full record

ArticleNPJ digital medicine2026

The landscape of artificial intelligence-enabled medical devices in the EU and the US intended for intensive care units.

Oscar Freyer, Stephan Buch, Adel Bassily-Marcus, Sven Zenker, Brian W Pickering, Max Ostermann, Anett Schönfelder, Stephen Gilbert

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital 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

8 authors.

Oscar FreyerElse Kröner Fresenius Center for Digital Health, TUD Dresden University of Technology, Dresden, Germany. oscar.freyer@tu-dresden.de.
Stephan BuchElse Kröner Fresenius Center for Digital Health, TUD Dresden University of Technology, Dresden, Germany.
Adel Bassily-MarcusYale School of Medicine, Department of Surgery, Yale New Haven Health System, New Haven, CT, USA.
Sven ZenkerStaff Unit for Medical & Scientific Technology Development & Coordination (MWTek), University Hospital Bonn, Bonn, Germany.
Brian W PickeringDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, NY, USA.
Max OstermannElse Kröner Fresenius Center for Digital Health, TUD Dresden University of Technology, Dresden, Germany.
Anett SchönfelderElse Kröner Fresenius Center for Digital Health, TUD Dresden University of Technology, Dresden, Germany.
Stephen GilbertElse Kröner Fresenius Center for Digital Health, TUD Dresden University of Technology, Dresden, Germany.

Funding

Bundesministerium für Forschung, Technologie und Raumfahrt 03ZU1210BAEuropean Commission 101094218
6 · The paper itself

Abstract

Artificial intelligence (AI) is increasingly used in healthcare, yet translation into routine intensive care units (ICU) practice remains slow. Through a multimethod search, we identified 36 on-market ICU-specific AI-enabled medical devices in the US and EU, challenging previous research findings. Most devices focus on prediction. However, as availability does not equal proven benefit, adoption will depend less on the availability of additional models and more on addressing persistent implementation barriers.

Identifiers

PMID41963517
PMCPMC13087237

What Socratic holds

Textmetadata
LicenceCC BY
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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.