Evidence map›Paper›PMID 41388183›Full record

ReviewInternal and emergency medicine2026

Artificial Intelligence in heart and brain ultrasound: the least you need to know.

Chiara Mozzini, Giuseppe Lucchini, Marko Bertogna, Alder Casadei, Mauro Pagani

Abstract readReview
PubMed Publisher
In one paragraph

Review in Internal and emergency medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

5 authors.

Chiara MozziniDepartment of Medicine, ASST Mantova, C. Poma Hospital Strada Lago Paiolo, 10 4600, Mantua, Italy. chiara.mozzini@asst-mantova.it.ORCID 0000-0002-4414-6576
Giuseppe LucchiniBiostatistic Unit, ASST Mantova, C. Poma Hospital Strada Lago Paiolo, 10 4600, Mantua, Italy.
Marko BertognaDepartment of Physics, Mathematics and Computer Science, University of Modena and Reggio Emilia, 41125, Modena, Italy.
Alder CasadeiUltrasound Association of South-Tyrol, Bolzano Health District, Bolzano, Italy.
Mauro PaganiDepartment of Medicine, ASST Mantova, C. Poma Hospital Strada Lago Paiolo, 10 4600, Mantua, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The application of Artificial Intelligence (AI) in medical imaging has demonstrated substantial potential in enhancing diagnostic accuracy, reducing inter-operator variability, and improving workflow efficiency. This review examines the integration of AI into three ultrasound pillars: echocardiography, carotid ultrasound, and transcranial Doppler (TCD). These techniques have long relied on expert interpretation, but AI-driven advancements now promise to revolutionize clinical practice by providing automated image analysis, improving diagnostic capabilities, and enhancing prognostic prediction. While echocardiography remains a cornerstone in the diagnosis of heart disease, carotid ultrasound and TCD are critical for assessing brain atherosclerosis and stroke risk and management. This narrative review explores AI applications in these domains, highlighting the current state of technology, clinical implications, challenges, and future prospects.

Indexed as

Artificial IntelligenceBrainHeartEchocardiographyHumansUltrasonographyUltrasonography, Doppler, TranscranialArtificial intelligenceCardiac ultrasoundTranscranial Doppler

Identifiers

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.