AIMC Topic: Dermatologists
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Understanding Dermatologists' Acceptance of Digital Health Interventions: Cross-Sectional Survey and Cluster Analysis.
JMIR human factors
May 21, 2025
BACKGROUND: Digital health interventions (DHIs) have the potential to enhance dermatological care by improving quality, patient empowerment, and efficiency. However, adoption remains limited, particularly in Germany.
Psychological Factors Influencing Appropriate Reliance on AI-enabled Clinical Decision Support Systems: Experimental Web-Based Study Among Dermatologists.
Journal of medical Internet research
Apr 4, 2025
BACKGROUND: Artificial intelligence (AI)-enabled decision support systems are critical tools in medical practice; however, their reliability is not absolute, necessitating human oversight for final decision-making. Human reliance on such systems can ...
Exploring the Views of Dermatologists, General Practitioners, and Melanographers on the Use of AI Tools in the Context of Good Decision-Making When Detecting Melanoma: Qualitative Interview Study.
JMIR dermatology
Mar 24, 2025
BACKGROUND: Evidence that artificial intelligence (AI) may improve melanoma detection has led to calls for increased human-AI collaboration in clinical workflows. However, AI-based support may entail a wide range of specific functions for AI. To appr...
Physician Level Assessment of Hirsute Women and of Their Eligibility for Laser Treatment With Deep Learning.
Lasers in surgery and medicine
Sep 22, 2024
OBJECTIVES: Hirsutism is a widespread condition affecting 5%-15% of females. Laser treatment of hirsutism has the best long-term effect. Patients with nonpigmented or nonterminal hairs are not eligible for laser treatment, and the current patient jou...
Grading facial aging: Comparing the clinical assessments made by three dermatologists with those obtained by an AI-based scoring system that analyses selfie pictures. A focus on Chinese subjects of both genders.
International journal of cosmetic science
Sep 1, 2024
OBJECTIVE: The objective of this study is to assess the correspondence, in live conditions, between clinical gradings of facial aging signs by three dermatologists and those afforded by an automatic AI-based algorithm that analyses smartphones' selfi...
Computerizing the first step of the two-step algorithm in dermoscopy: A convolutional neural network for differentiating melanocytic from non-melanocytic skin lesions.
European journal of cancer (Oxford, England : 1990)
Aug 25, 2024
IMPORTANCE: Convolutional neural networks (CNN) have shown performance equal to trained dermatologists in differentiating benign from malignant skin lesions. To improve clinicians' management decisions, additional classifications into diagnostic cate...
Patients' and dermatologists' preferences in artificial intelligence-driven skin cancer diagnostics: A prospective multicentric survey study.
Journal of the American Academy of Dermatology
Apr 24, 2024
Comparing preferences for skin cancer screening: AI-enabled app vs dermatologist.
Social science & medicine (1982)
Apr 15, 2024
BACKGROUND AND AIM: Skin cancer is a major public health issue. While self-examinations and professional screenings are recommended, they are rarely performed. Mobile health (mHealth) apps utilising artificial intelligence (AI) for skin cancer screen...
Patient and dermatologists' perspectives on augmented intelligence for melanoma screening: A prospective study.
Journal of the European Academy of Dermatology and Venereology : JEADV
Feb 27, 2024
BACKGROUND: Artificial intelligence (AI) shows promising potential to enhance human decision-making as synergistic augmented intelligence (AuI), but requires critical evaluation for skin cancer screening in a real-world setting.
The performance of an artificial intelligence-based computer vision mobile application for the image diagnosis of genital dermatoses: a prospective cross-sectional study.
International journal of dermatology
Feb 5, 2024
BACKGROUND: There is a huge demand-supply gap between the incidence of genital dermatoses (including sexually transmitted infections and non-venereal genital dermatoses) and physicians trained to manage them.
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