dc.contributor.author
Busch, Felix
dc.contributor.author
Han, Tianyu
dc.contributor.author
Makowski, Marcus R
dc.contributor.author
Truhn, Daniel
dc.contributor.author
Bressem, Keno K
dc.contributor.author
Adams, Lisa
dc.date.accessioned
2025-07-28T15:30:04Z
dc.date.available
2025-07-28T15:30:04Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/48444
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-48166
dc.description.abstract
This study demonstrates that GPT-4V outperforms GPT-4 across radiology subspecialties in analyzing 207 cases with 1312 images from the Radiological Society of North America Case Collection.
en
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Generative Pre-Trained Transformer
en
dc.subject
multimodal large language models
en
dc.subject
artificial intelligence
en
dc.subject
AI applications in medicine
en
dc.subject
diagnostic radiology
en
dc.subject
clinical decision support systems
en
dc.subject
generative AI
en
dc.subject
medical image analysis
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit
dc.title
Integrating Text and Image Analysis: Exploring GPT-4V’s Capabilities in Advanced Radiological Applications Across Subspecialties
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
e54948
dcterms.bibliographicCitation.doi
10.2196/54948
dcterms.bibliographicCitation.journaltitle
Journal of Medical Internet Research
dcterms.bibliographicCitation.originalpublishername
JMIR Publications
dcterms.bibliographicCitation.volume
26
refubium.affiliation
Charité - Universitätsmedizin Berlin
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.bibliographicCitation.pmid
38691404
dcterms.isPartOf.eissn
1438-8871
