Litcius/Paper detail

Perceptions of Artificial Intelligence Integration into Dermatology Clinical Practice: A Cross-Sectional Survey Study

Chapman Wei, Nagasai Adusumilli, Adam Friedman, Vishal Patel

2022Journal of Drugs in Dermatology16 citationsDOI

Abstract

BACKGROUND: Artificial intelligence (AI) is a growing field in dermatology and has great potential for integration into clinical practice. Our objective was to assess the perceptions of artificial intelligence in dermatology practice. METHODS: An IRB-approved 18-question online survey was distributed by email. Patients were stratified by age to assess for statistical differences among perceptions. RESULTS: 90 respondents fully completed the survey. 54 (60.0%) respondents were slightly familiar with AI, and 73 (81.1%) respondents have not incorporated AI into their clinical practice. 27.8% of respondents perceived AI as superior to a human provider’s experience some of the time. 94.4% of respondents would at least use AI for certain scenarios. 65.6% of respondents believed that AI would help patients with analyzing and managing electronic health records. 38.9% respondents predict that AI will not decrease or increase the need for dermatologists. 51.6% of respondents felt that AI will at least somewhat enhance the dermatologists’ ability to screen skin lesions. The three dermatology areas that AI was perceived to most beneficial were malignant skin lesions, benign skin lesions, and pigmentation disorders. Age of respondents did not have a significant impact on the perceptions of AI. CONCLUSION: Our results show that dermatologists surveyed were generally positive toward embracing AI integration into clinical practice. Further studies should be conducted to confirm these findings. J Drugs Dermatol. 2022;21(2):135-140. doi:10.36849/JDD.6398.

Topics & Concepts

MedicineDermatologyCross-sectional studyClinical PracticePerceptionFamily medicinePathologyPsychologyNeuroscienceCutaneous Melanoma Detection and ManagementArtificial Intelligence in Healthcare and EducationGenomics and Rare Diseases