Framing Bias in a Large Language Model: A Diagnostic Accuracy Study of Prompt Effects on ChatGPT’s Melanoma Classification
Published: 18 November 2025| Version 1 | DOI: 10.17632/tpcf29wdzj.1
Contributors:
, , , Description
- Mendeley Supplemental Figure 1. Representative examples of the test. Each image was presented six times under different instructions: a neutral baseline prompt, and five framed prompts. - Mendeley Supplemental File 1. Detailed Materials and methods (Study design, Model Access and Interaction, Dataset Details, Prompting Procedure, Outcome Measures and Statistical Analysis) of the study
Files
Institutions
Universita Cattolica del Sacro Cuore
Categories
Artificial Intelligence, Dermatology, Melanoma, Large Language Model
Funding
None
Additional Metadata for UCSC Datasets
| Campus | Rome |
| Scientific Disciplinary Area (after 2024) | MEDS-10/C - Dermatology and Venereal Diseases |