Evidence map›Paper›PMID 41438080›Full record

ArticleiScience2025

Machine learning enhanced noninvasive transcranial stroke detection using a portable eddy current damping sensor.

Haixu Shen, Seyed Mohammadreza Ghodsi, Benjamin Fixman, Bita Ghodsi, Kirsten Azarraga, Narendhar Prasad, Shane Shahrestani, Nerses Sanossian, Gabriel Zada, Yu-Chong Tai

Abstract read
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In one paragraph

Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Haixu ShenDepartment of Medical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
Seyed Mohammadreza GhodsiDepartment of Neurosurgery, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA.
Benjamin FixmanDepartment of Neurosurgery, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA.
Bita GhodsiDepartment of Mathematics, Western University, London, ON N6A 5B7, Canada.
Kirsten AzarragaDepartment of Bioengineering, University of Southern California, Los Angeles, CA 90089, USA.
Narendhar PrasadDepartment of Bioengineering, University of Southern California, Los Angeles, CA 90089, USA.
Shane ShahrestaniDepartment of Neurosurgery, Cedars Sinai, Los Angeles, CA 90048, USA.
Nerses SanossianDepartment of Neurology, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA.
Gabriel ZadaDepartment of Neurosurgery, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA.
Yu-Chong TaiDepartment of Medical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.

Funding

Noninvasive transcranial detection of intracranial hemorrhage using a tri-coil handheld portable eddy current damping imaging deviceR01NS119596 · NINDS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ZADA, GABRIEL · 2021 to 2025
$1.9M
NINDS NIH HHS R01 NS119596
6 · The paper itself

Abstract

Stroke remains a leading cause of morbidity and mortality globally, with timely diagnosis critical for effective treatment. Current imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), often face limitations in availability and timeliness, leading to diagnostic delays that worsen patient outcomes. This study presents the development and validation of a portable, noninvasive eddy current damping (ECD) sensor for rapid stroke detection. Building on previous research and optimized through benchtop and phantom studies, this device incorporates advanced coil designs and algorithms to distinguish between hemorrhagic stroke patients and healthy individuals by detecting electrical conductivity variations between normal brain tissue and accumulated blood. Results demonstrate high degrees of accuracy and specificity, promising to enable real-time bedside differentiation of stroke patients. This ECD sensor may expand access to timely stroke care across prehospital, clinical, and remote settings and improve patient outcomes by expediting targeted treatment and rapid triage.

Indexed as

Bioelectronics

Identifiers

PMID41438080
PMCPMC12719177

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.