Applications of Machine Learning, Natural Language Processing, and Generative Artificial Intelligence in Dermatology Education and Research: A Scoping Review.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος:	Applications of Machine Learning, Natural Language Processing, and Generative Artificial Intelligence in Dermatology Education and Research: A Scoping Review.
Συγγραφείς:	Lau LDW; Department of Dermatology, Western Health, St Albans, Victoria, Australia., Tran V; Department of Dermatology, Royal Melbourne Hospital, Parkville, Victoria, Australia., Chapman W; Centre for Clinical Informatics, The University of Texas Southwestern Medical Centre, Dallas, USA.; Centre for Digital Transformation of Health, The University of Melbourne, Melbourne, Australia., Morgan V; Department of Dermatology, Royal Melbourne Hospital, Parkville, Victoria, Australia., Scardamaglia L; Department of Dermatology, Western Health, St Albans, Victoria, Australia.; Department of Dermatology, Royal Melbourne Hospital, Parkville, Victoria, Australia.; Department of Medicine, University of Melbourne, Parkville, Victoria, Australia., Ross G; Department of Dermatology, Royal Melbourne Hospital, Parkville, Victoria, Australia.; Department of Medicine, University of Melbourne, Parkville, Victoria, Australia., Wong CC; Department of Dermatology, Royal Melbourne Hospital, Parkville, Victoria, Australia.; Department of Medicine, University of Melbourne, Parkville, Victoria, Australia.; Department of Dermatology, Monash Health, Clayton, Victoria, Australia.
Πηγή:	International journal of dermatology [Int J Dermatol] 2026 Aug; Vol. 65 (8), pp. 1600-1610. Date of Electronic Publication: 2026 Apr 14.
Τύπος έκδοσης:	Journal Article; Scoping Review
Γλώσσα:	English
Στοιχεία περιοδικού:	Publisher: Blackwell Science Country of Publication: England NLM ID: 0243704 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1365-4632 (Electronic) Linking ISSN: 00119059 NLM ISO Abbreviation: Int J Dermatol Subsets: MEDLINE
Imprint Name(s):	Publication: Oxford : Blackwell Science Original Publication: Philadelphia, Lippincott.
Ιατρικοί όροι (MeSH):	Biomedical Research/methods , Dermatology/education , Artificial Intelligence* , Machine Learning* , Natural Language Processing*, Humans ; Data Mining ; Generative Artificial Intelligence ; Large Language Models
Περίληψη:	Artificial intelligence (AI) is being increasingly used in dermatology education and research as digital health data expands and large language models (LLMs) advance. This scoping review synthesized current applications, benefits, and limitations of AI in these domains. The review followed PRISMA-ScR methodology, including 102 studies published between 2010 and 2025, with 28 studies examining educational applications and 74 examining research applications. Educational applications included the use of LLMs for examination preparation, question and case generation, and image-based learning through generative and adaptive imaging tools. Research applications included machine learning and natural language processing for large-scale data analysis, pharmacovigilance, social media and clinical text mining, predictive modeling, biomarker and gene-signature discovery, and the use of LLMs to support literature synthesis, manuscript writing, and research workflow tasks. Across education and research, key limitations related to accuracy, bias, transparency, and ethical governance. These issues highlight the need for ongoing human oversight, the use of dermatology-specific training datasets, and structured implementation frameworks. Despite these considerations, AI has substantial potential to enhance dermatology learning and improve dermatologic research efficiency. Future work should focus on evaluating real-world performance, model reliability, and the effectiveness of human-AI collaboration in dermatology practice and training. (© 2026 the International Society of Dermatology.)
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Contributed Indexing:	Keywords: artificial intelligence; dermatology; education; machine learning; natural language processing; research
Entry Date(s):	Date Created: 20260415 Date Completed: 20260708 Latest Revision: 20260727
Update Code:	20260727
DOI:	10.1111/ijd.70418
PMID:	41981908
Βάση Δεδομένων:	MEDLINE

Περιγραφή
ISSN:	1365-4632
DOI:	10.1111/ijd.70418