Evidence map›Paper›PMID 41622253›Full record

ArticleScientific reports2026

Smart, automated junctional tourniquets leveraging AI-driven ultrasound guidance.

Sofia I Hernandez Torres, Theodore Winter, Isiah Mejia, Carlos Bedolla, Benjamin Alexander, James P Collier, Michael D Lopez, Eric J Snider

Abstract read
In one paragraph

Article in Scientific reports, 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.

Sofia I Hernandez TorresU.S. Army Institute of Surgical Research, Organ Support and Automation Technologies Group, JBSA Fort Sam Houston, San Antonio, TX, 78234, USA.
Theodore WinterU.S. Army Institute of Surgical Research, Organ Support and Automation Technologies Group, JBSA Fort Sam Houston, San Antonio, TX, 78234, USA.
Isiah MejiaU.S. Army Institute of Surgical Research, Organ Support and Automation Technologies Group, JBSA Fort Sam Houston, San Antonio, TX, 78234, USA.
Carlos BedollaU.S. Army Institute of Surgical Research, Organ Support and Automation Technologies Group, JBSA Fort Sam Houston, San Antonio, TX, 78234, USA.
Benjamin AlexanderU.S. Army Institute of Surgical Research, Organ Support and Automation Technologies Group, JBSA Fort Sam Houston, San Antonio, TX, 78234, USA.
James P CollierU.S. Army Institute of Surgical Research, Organ Support and Automation Technologies Group, JBSA Fort Sam Houston, San Antonio, TX, 78234, USA.
Michael D LopezU.S. Army Institute of Surgical Research, Organ Support and Automation Technologies Group, JBSA Fort Sam Houston, San Antonio, TX, 78234, USA.
Eric J SniderU.S. Army Institute of Surgical Research, Organ Support and Automation Technologies Group, JBSA Fort Sam Houston, San Antonio, TX, 78234, USA. eric.j.snider3.civ@health.mil.

Funding

U.S. Department of Defense DPSI
6 · The paper itself

Abstract

Tourniquets are commonly used devices for hemorrhage control; however, their effectiveness is reduced in anatomical junctions such as the neck and inguinal region. Junctional tourniquets specifically require precise placement to be effective. This precision can be enabled with ultrasound technology to help locate and occlude the major vessels in the junctional regions properly. However, interpretation of ultrasound requires highly skilled personnel, who may not necessarily be available in emergency situations. To overcome this hurdle, we have developed two ultrasound-enabled, AI-driven junctional tourniquet prototypes. AI models can aid in guiding the end-user to the correct location and determine occlusion during and after pressure application. Proof-of-concept functionality of the developed prototypes integrated with AI models was successfully tested in a durable, ultrasound-compatible femoral tissue phantom and compared against commercially available tourniquet devices. Overall, time to occlusion was comparable between the tourniquet prototype designs and traditional junctional tourniquets, while each AI model achieved high performance metrics for this application. As such, the combination of AI and ultrasound can prove to be a viable solution to prevent further hemorrhaging at the point of injury.

Indexed as

HemorrhageTourniquetsEquipment DesignHumansIntelligent SystemsPhantoms, ImagingUltrasonography

Identifiers

PMID41622253
PMCPMC12916782

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.