AIMC Topic: Dermatology

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Leveraging AI Large Language Models for Writing Clinical Trial Proposals in Dermatology: Instrument Validation Study.

JMIR dermatology
BACKGROUND: Large language models (LLMs) are becoming increasingly popular in clinical trial design but have been underused in research proposal development.

Image Generation of Common Dermatological Diagnoses by Artificial Intelligence: Evaluation Study of the Potential for Education and Training Purposes.

JMIR dermatology
BACKGROUND: The integration of artificial intelligence (AI) into dermatology holds promise for education and diagnostic purposes, particularly through image generation, which has not been well studied.

Evaluating Artificial Intelligence Models in Dermatology: Comparative Analysis.

JMIR dermatology
DermGPT demonstrated strong potential for improving answer clarity and conciseness in dermatology-related queries, while ChatGPT provided more robust source citations, enhancing trust in evidence-based responses.

Artificial intelligence for skin lesion classification and diagnosis in dermatology: A narrative review.

Medwave
INTRODUCTION: Artificial intelligence (AI) is increasingly present in dermatology, demonstrating accuracy levels comparable to, or even superior to, those of dermatologists in diagnosing skin lesions from clinical and dermoscopic images. This review ...

Ethical challenges in biomarker research and precision medicine - a qualitative study in dermatology.

BMC medical ethics
BACKGROUND: Over 300 million individuals worldwide live with Atopic Dermatitis and Psoriasis, which are among the most common chronic inflammatory skin diseases. Multimodal biomarkers are currently being developed using large-scale data and artificia...

Teledermatology to Support Self-Care in Chronic Spontaneous Urticaria.

JMIR dermatology
Chronic spontaneous urticaria (CSU) is an autoimmune prompted skin disorder, whose hallmarks include the unpredictable onset of hives and itch. Symptom duration typically exceed 6 weeks, and flares can occur for up to 5 years or longer if untreated, ...

A methodology for developing dermatological datasets: lessons from retrospective data collection for AI-based applications.

BMC medical research methodology
PURPOSE: The integration of artificial intelligence into dermatological research has underscored the need for robust and well-structured dermatological datasets. However, these datasets vary widely in their development processes, and there is current...

Use of a Large Language Model as a Dermatology Case Narrator: Exploring the Dynamics of a Chatbot as an Educational Tool in Dermatology.

JMIR dermatology
A comparison of dermatological cases generated by artificial intelligence (AI) versus those created without AI by medical students revealed that AI-created cases were characterized by detailed case descriptions, analysis of medical history, and clini...

Patient Perceptions of Artificial Intelligence and Telemedicine in Dermatology: Narrative Review.

JMIR dermatology
BACKGROUND: Artificial intelligence (AI) and telemedicine have significant potential to transform dermatology care delivery, but patient perspectives on these technologies have not been systematically compared.