Evidence map›Paper›PMID 38294325›Full record

ArticleRadiology. Artificial intelligence2024

Performance of ChatGPT on the Brazilian Radiology and Diagnostic Imaging and Mammography Board Examinations.

Leonardo C Almeida, Eduardo M J M Farina, Paulo E A Kuriki, Nitamar Abdala, Felipe C Kitamura

Open access · greenAbstract read
In one paragraph

Article in Radiology. Artificial intelligence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.8field-weighted citation impact, top 11% of its field
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

21 citing papers in PubMed, 47 citations in OpenAlex.

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  15. [Large Language Models: A Comprehensive Guide for Radiologists].Journal of the Korean Society of Radiology · 2024
    Review
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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 at 1 institution in 1 country.

Leonardo C AlmeidaFrom the Department of Artificial Intelligence and Management (L.C.A., E.M.J.M.F., N.A., F.C.K.), Graduate Program in Medicine (Clinical Radiology), Universidade Federal de São Paulo (UNIFESP), Rua Botucatu, 740, 04023-062, São Paulo, São Paulo, Brazil; AI Lab (L.C.A., E.M.J.M.F., P.E.A.K., F.C.K.), Dasa, São Paulo, São Paulo, Brazil.ORCID 0009-0002-2634-9027
Eduardo M J M FarinaFrom the Department of Artificial Intelligence and Management (L.C.A., E.M.J.M.F., N.A., F.C.K.), Graduate Program in Medicine (Clinical Radiology), Universidade Federal de São Paulo (UNIFESP), Rua Botucatu, 740, 04023-062, São Paulo, São Paulo, Brazil; AI Lab (L.C.A., E.M.J.M.F., P.E.A.K., F.C.K.), Dasa, São Paulo, São Paulo, Brazil.ORCID 0000-0002-3935-6077
Paulo E A KurikiFrom the Department of Artificial Intelligence and Management (L.C.A., E.M.J.M.F., N.A., F.C.K.), Graduate Program in Medicine (Clinical Radiology), Universidade Federal de São Paulo (UNIFESP), Rua Botucatu, 740, 04023-062, São Paulo, São Paulo, Brazil; AI Lab (L.C.A., E.M.J.M.F., P.E.A.K., F.C.K.), Dasa, São Paulo, São Paulo, Brazil.ORCID 0000-0002-1485-5750
Nitamar Abdala *From the Department of Artificial Intelligence and Management (L.C.A., E.M.J.M.F., N.A., F.C.K.), Graduate Program in Medicine (Clinical Radiology), Universidade Federal de São Paulo (UNIFESP), Rua Botucatu, 740, 04023-062, São Paulo, São Paulo, Brazil; AI Lab (L.C.A., E.M.J.M.F., P.E.A.K., F.C.K.), Dasa, São Paulo, São Paulo, Brazil.ORCID 0000-0002-0421-0959
Felipe C Kitamura *From the Department of Artificial Intelligence and Management (L.C.A., E.M.J.M.F., N.A., F.C.K.), Graduate Program in Medicine (Clinical Radiology), Universidade Federal de São Paulo (UNIFESP), Rua Botucatu, 740, 04023-062, São Paulo, São Paulo, Brazil; AI Lab (L.C.A., E.M.J.M.F., P.E.A.K., F.C.K.), Dasa, São Paulo, São Paulo, Brazil.ORCID 0000-0002-9992-5630
Universidade Federal de São Paulo · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This prospective exploratory study conducted from January 2023 through May 2023 evaluated the ability of ChatGPT to answer questions from Brazilian radiology board examinations, exploring how different prompt strategies can influence performance using GPT-3.5 and GPT-4. Three multiple-choice board examinations that did not include image-based questions were evaluated:

Indexed as

Artificial IntelligenceRadiologyBrazilMammographyProspective StudiesRadiographyArtificial IntelligenceBoard ExaminationsChatGPTMammographyNeuroradiologyRadiology and Diagnostic Imaging

Identifiers

PMID38294325
PMCPMC10831524
OpenAlexW4388489982

What OpenQuestion 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 OpenQuestion graph.