Evidence map›Paper›PMID 37547892›Full record

ReviewMethodist DeBakey cardiovascular journal2023

Emerging Applications for Computer Vision and Artificial Intelligence in Management of the Cardiovascular Patient.

Peter Osztrogonacz, Ponraj Chinnadurai, Alan B Lumsden

Abstract readReview
In one paragraph

Review in Methodist DeBakey cardiovascular journal, 2023. 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. Article
  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

3 authors.

Peter OsztrogonaczMethodist DeBakey Heart & Vascular Center, Houston Methodist, Houston, Texas, US.ORCID https://orcid.org/0000-0002-5633-4363
Ponraj ChinnaduraiOccam Labs, London, UK.ORCID https://orcid.org/0000-0001-9223-1284
Alan B LumsdenMethodist DeBakey Heart & Vascular Center, Houston Methodist, Houston, Texas, US.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence and telemedicine promise to reshape patient care to an unprecedented extent, leading to a safer and more sustainable work environment and improved patient care. In this article, we summarize how these emerging technologies can be used in the care of cardiovascular patients in such ways as fall detection and prevention, virtual nursing, remote case support, automation of instrument counts in the operating room, and efficiency optimization in the cardiovascular suite.

Indexed as

Artificial IntelligenceTelemedicineComputersHumansAIartificial intelligencemental workloadtelemedicinetelenursing

Identifiers

PMID37547892
PMCPMC10402826

What OpenQuestion 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 OpenQuestion graph.