AIMC Topic: Dermatology
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Urgency vs triage prioritisation: appropriateness of referrer-rated urgency of referrals to a public dermatology service.
The New Zealand medical journal
Jun 27, 2025
AIM: To characterise the appropriateness of community referrer-rated urgency among dermatology referrals.
Artificial Intelligence in Patch Testing: Comprehensive Review of Current Applications and Future Prospects in Dermatology.
JMIR dermatology
Jun 2, 2025
BACKGROUND: The integration of artificial intelligence (AI) into patch testing for allergic contact dermatitis (ACD) holds the potential to standardize diagnoses, reduce interobserver variability, and improve overall diagnostic accuracy. However, the...
Closing the AI generalisation gap by adjusting for dermatology condition distribution differences across clinical settings.
EBioMedicine
Jun 2, 2025
BACKGROUND: Generalisation of artificial intelligence (AI) models to a new setting is challenging. In this study, we seek to understand the robustness of a dermatology (AI) model and whether it generalises from telemedicine cases to a new setting inc...
Generating dermatopathology reports from gigapixel whole slide images with HistoGPT.
Nature communications
May 27, 2025
Histopathology is the reference standard for diagnosing the presence and nature of many diseases, including cancer. However, analyzing tissue samples under a microscope and summarizing the findings in a comprehensive pathology report is time-consumin...
Evaluating medical AI systems in dermatology under uncertain ground truth.
Medical image analysis
Apr 9, 2025
For safety, medical AI systems undergo thorough evaluations before deployment, validating their predictions against a ground truth which is assumed to be fixed and certain. However, in medical applications, this ground truth is often curated in the f...
A Systemic Review of Large Language Models and Their Implications in Dermatology.
The Australasian journal of dermatology
Apr 6, 2025
In computational linguistics, large language models have reached a significant turning point. They have quickly spread throughout several sectors, including the medical field. By integrating demographics, clinical photos, medical interviews, or genet...
Predictive modeling and optimization in dermatology: Machine learning for skin disease classification.
Computers in biology and medicine
Mar 3, 2025
The accurate diagnosis of skin diseases is crucial for effective patient management and treatment, yet traditional diagnostic methods often involve subjective interpretation and can lead to variability in outcomes. In this study, we harness the power...
The good, the bad, and the ugly: Ethical considerations regarding artificial intelligence assistance in administrative physician tasks.
Clinics in dermatology
Feb 11, 2025
Artificial intelligence is a powerful tool that can potentially transform the diagnostic, therapeutic, and administrative practice of dermatology. Physicians are expected to complete electronic health record documentation in a timely fashion, prepare...
The use of a ChatGPT-4-based chatbot in teledermatology: A retrospective exploratory study.
Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG
Jan 12, 2025
BACKGROUND AND OBJECTIVES: Integration of artificial intelligence in healthcare, particularly ChatGPT, is transforming medical diagnostics and may benefit teledermatology. This exploratory study compared image description and differential diagnosis g...
Enhancing Spanish Patient Education Materials: Comparing the Readability of Artificial Intelligence-Generated Spanish Patient Education Materials to the Society of Pediatric Dermatology Spanish Patient Brochures.
Pediatric dermatology
Nov 12, 2024
Patient education materials (PEMs) are crucial for improving patient adherence and outcomes; however, they may not be accessible due to high reading levels. Our study used seven readability measures to compare the readability of Spanish PEMs from the...
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