Utilizing artificial intelligence to address dermatology curriculum deficiencies in pre-clinical medical education
Year: 2025
Type: article
Abstract: There are deficiencies in preclinical dermatology education: only 12% of medical schools in the United States offer a dedicated preclinical curriculum. Students could use free artificial intelligence as an alternative to other expensive resources to prepare for United States Medical Licensing Examination board examinations. ChatGPT was prompted to generate a dermatology curriculum including lecture outlines, disease pathology, histology, pharmacology, and practice questions based on the United States Medical Licensing Examination Step 1 content outline. The result was analyzed for completeness, accuracy, and quality. ChatGPT created a dermatology curriculum with 8 topics: introduction, infectious disorders, inflammatory disorders, neoplasms, integumentary disorders, pathology/histology, pharmacology, and clinical case studies. The curriculum included placeholders for the visual learning components rather than incorporating clinical images. The clinical vignettes included were incomplete and not detailed. Artificial intelligence can provide accessible, personalized, and cost-effective resources for preclinical medical students learning dermatology. This has the potential to impact inequalities among medical schools in dermatology education. However, generated curriculums need to be evaluated by dermatology educators to ensure accuracy and quality.
Source: Dermatology Online Journal
DOI: 10.25251/70k6fb79
Authors: Lauren McGrath, Melanie Rodriguez, Maria Mariencheck, Steven Feldman, Zeynep Akkurt
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $300
OpenAlex ID: W4415489437
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