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Establishing Research Priorities for Artificial Intelligence Approaches in Dermatology Using an e-Delphi Exercise
Ravi Ramessur1,2, Luke Carson3,4, Joseph Scott5,6
1St John's Institute of Dermatology, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK.
Clinical and Experimental Dermatology
|May 18, 2026
Summary
This study identified clinician priorities for artificial intelligence (AI) in dermatology. Top priorities include skin cancer diagnostics and, when excluded, focus on triage, efficiency, and equity in AI applications.
Area of Science:
- Dermatology
- Artificial Intelligence
- Health Informatics
Background:
- Most artificial intelligence (AI) research in dermatology focuses on image-based skin cancer diagnostics.
- Broader AI applications and their alignment with clinical priorities are underexplored.
- Understanding clinician priorities is crucial for developing relevant and equitable AI tools in dermatology.
Purpose of the Study:
- To identify and prioritize clinician-generated research questions for AI in dermatology.
- Utilized an international, consensus-based electronic Delphi (e-Delphi) study approach.
Main Methods:
- A three-round e-Delphi study involved dermatologists and other clinicians.
- Participants submitted and prioritized research questions across ten domains.
- A steering group refined questions, and participants rated them using a Likert scale.
Main Results:
- 101-150 clinicians participated, submitting 429 questions refined into 110 items.
- Highest priorities centered on skin cancer diagnostics and monitoring.
- Excluding cancer topics, priorities shifted to triage, workflow efficiency, primary care support, communication, and diagnostic equity.
Conclusions:
- This study establishes clinician-led priorities for AI research in dermatology.
- Findings offer a roadmap for aligning AI development with clinical needs.
- Aims to foster equitable, efficient, and relevant AI innovation in dermatology.
