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Artificial Intelligence in Dermatology Among Saudi Adults: Cross-Sectional Survey Study
Shada Khalid Alanazi1, Lama Nawaf Alanazi1, Zahra Saleh Alsindi1
1College of Medicine, King Faisal University, Al-Ahsa 31982, Saudi Arabia.
Healthcare (Basel, Switzerland)
|July 15, 2026
Summary
Saudi adults show moderately positive but cautious attitudes towards artificial intelligence (AI) in dermatology. Public trust in AI for skin health hinges on physician supervision, data privacy, and accuracy.
Area of Science:
- Dermatology
- Artificial Intelligence
- Public Health
Background:
- Artificial intelligence (AI) offers potential for enhanced dermatological diagnostics and care access.
- Public trust and acceptance are critical for successful AI adoption in healthcare.
- Understanding Saudi adults' perspectives on AI in dermatology is essential for its integration.
Purpose of the Study:
- To assess knowledge, attitudes, and acceptance of dermatological AI among Saudi adults.
- To identify factors influencing adoption, trust, and preferred AI system characteristics.
- To inform strategies for responsible AI implementation in Saudi dermatology.
Main Methods:
- A nationwide cross-sectional online survey was conducted among 668 Saudi adults.
- Data collection utilized social media platforms for convenience and snowball sampling.
- Analysis involved descriptive statistics, ANOVA, and binary logistic regression.
Main Results:
- Overall AI attitude orientation was moderately positive but conditional (mean score 74.48 ± 10.20).
- Physician-supervised AI was strongly preferred over autonomous systems; medical oversight was highly valued (mean 4.27 ± 0.87).
- Privacy protection and diagnostic accuracy were key concerns; younger age and tech interest correlated with favorable attitudes.
Conclusions:
- Saudi adults exhibit favorable yet cautious attitudes towards dermatological AI.
- Implementation should prioritize physician oversight, transparency, and data privacy.
- Culturally responsive design is crucial for responsible integration of AI in clinical practice.
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