Digitizing Diagnoses: Distinguishing Infantile Hemangiomas From Other Vascular Anomalies
This off-the-shelf publicly available GPT (75%) was less accurate than a previously published well-trained AI that achieved higher accuracy (~92%). GPT's F1 score of 0.742 indicates moderate balance between precision and sensitivity, and an AUC calculation of 0.80 indicates a potential role for GPT as a clinical assistant in primary care settings. An untuned commercial GPT does not yet outperform pediatricians despite studies of well-trained AI. This study provides variables impacting GPT accuracy, serving as a foundation for future research.
Authors
- Elena Huang (ORCID: https://orcid.org/0000-0002-4727-344X)
- James R. Hills
- Albert C. Yan (ORCID: https://orcid.org/0000-0002-8403-8780)
- Aretha On
- Griffin Stockton Hogrogian (ORCID: https://orcid.org/0000-0003-2877-078X)
- Joseph F. Pasternak
- Joanne Alfandre
Institutions
- Children's Hospital of Philadelphia (US)
- University of Pennsylvania (US)
Publication Details
- Journal
- Pediatric Dermatology
- Published
- 2025-08-14
- DOI
- https://doi.org/10.1111/pde.70008
- Citations
- 3
- Primary Topic
- Vascular Malformations and Hemangiomas
- Type
- article
- Field-Weighted Citation Impact
- 6.02