Evidence map›Paper›PMID 35136337›Full record

ReviewFederal practitioner : for the health care professionals of the VA, DoD, and PHS2021

Artificial Intelligence: Review of Current and Future Applications in Medicine.

L Brannon Thomas, Stephen M Mastorides, Narayan A Viswanadhan, Colleen E Jakey, Andrew A Borkowski

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Federal practitioner : for the health care professionals of the VA, DoD, and PHS, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
–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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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.

L Brannon ThomasJames A. Haley Veterans' Hospital, Tampa, Florida.
Stephen M MastoridesJames A. Haley Veterans' Hospital, Tampa, Florida.
Narayan A ViswanadhanJames A. Haley Veterans' Hospital, Tampa, Florida.
Colleen E JakeyJames A. Haley Veterans' Hospital, Tampa, Florida.
Andrew A BorkowskiJames A. Haley Veterans' Hospital, Tampa, Florida.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe role of artificial intelligence (AI) in health care is expanding rapidly. Currently, there are at least 29 US Food and Drug Administration-approved AI health care devices that apply to numerous medical specialties and many more are in development. OBSERVATIONS: With increasing expectations for all health care sectors to deliver timely, fiscally-responsible, high-quality health care, AI has potential utility in numerous areas, such as image analysis, improved workflow and efficiency, public health, and epidemiology, to aid in processing large volumes of patient and medical data. In this review, we describe basic terminology, principles, and general AI applications relating to health care. We then discuss current and future applications for a variety of medical specialties. Finally, we discuss the future potential of AI along with the potential risks and limitations of current AI technology.

conclusionsAI can improve diagnostic accuracy, increase patient safety, assist with patient triage, monitor disease progression, and assist with treatment decisions.

Identifiers

PMID35136337
PMCPMC8815615

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.