Actinic keratosis (AK) is a common ultraviolet (UV)-inducedprecancerous skin lesion that may progress to squamous cellcarcinoma (SCC), a potentially invasive malignancy [1, 2].Clinically differentiating between AK and SCC is challengingdue to overlapping features [3]. With the rise of accessible mul-timodal large language models (LLMs), patients now have ar-tificial intelligence (AI) tools such as ChatGPT to assess theirskin lesions at home. However, the diagnostic reliability of thesemodels in distinguishing AK from SCC remains unclear. Thisstudy evaluates and compares two advanced LLMs in identify-ing and differentiating between AK and SCC using real-worldclinical images

Diagnosing Actinic Keratosis and Squamous Cell Carcinoma With Large Language Models From Clinical Images / Boostani, Mehdi; Pellacani, Giovanni; Goldust, Mohamad; Nádudvari, Nóra; Rátky, Dóra; Cantisani, Carmen; Lőrincz, Kende; Bánvölgyi, András; Wikonkál, Norbert M; Paragh, Gyorgy; Kiss, Norbert. - In: INTERNATIONAL JOURNAL OF DERMATOLOGY. - ISSN 1365-4632. - (2025). [10.1111/ijd.18000]

Diagnosing Actinic Keratosis and Squamous Cell Carcinoma With Large Language Models From Clinical Images

Pellacani, Giovanni;Cantisani, Carmen;
2025

Abstract

Actinic keratosis (AK) is a common ultraviolet (UV)-inducedprecancerous skin lesion that may progress to squamous cellcarcinoma (SCC), a potentially invasive malignancy [1, 2].Clinically differentiating between AK and SCC is challengingdue to overlapping features [3]. With the rise of accessible mul-timodal large language models (LLMs), patients now have ar-tificial intelligence (AI) tools such as ChatGPT to assess theirskin lesions at home. However, the diagnostic reliability of thesemodels in distinguishing AK from SCC remains unclear. Thisstudy evaluates and compares two advanced LLMs in identify-ing and differentiating between AK and SCC using real-worldclinical images
2025
Diagnosing Actinic Keratosis
01 Pubblicazione su rivista::01a Articolo in rivista
Diagnosing Actinic Keratosis and Squamous Cell Carcinoma With Large Language Models From Clinical Images / Boostani, Mehdi; Pellacani, Giovanni; Goldust, Mohamad; Nádudvari, Nóra; Rátky, Dóra; Cantisani, Carmen; Lőrincz, Kende; Bánvölgyi, András; Wikonkál, Norbert M; Paragh, Gyorgy; Kiss, Norbert. - In: INTERNATIONAL JOURNAL OF DERMATOLOGY. - ISSN 1365-4632. - (2025). [10.1111/ijd.18000]
File allegati a questo prodotto
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1747038
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 4
social impact