AIMC Topic: Skin Diseases

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Efficacy of an Artificial Intelligence App (Aysa) in Dermatological Diagnosis: Cross-Sectional Analysis.

JMIR dermatology
BACKGROUND: Dermatology is an ideal specialty for artificial intelligence (AI)-driven image recognition to improve diagnostic accuracy and patient care. Lack of dermatologists in many parts of the world and the high frequency of cutaneous disorders a...

Deep Deblurring in Teledermatology: Deep Learning Models Restore the Accuracy of Blurry Images' Classification.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Blurry images in teledermatology and consultation increased the diagnostic difficulty for both deep learning models and physicians. We aim to determine the extent of restoration in diagnostic accuracy after blurry images are deblurred by deep learni...

Underserved populations and health equity in dermatology: Digital medicine and the role of artificial intelligence.

Clinics in dermatology
We have reviewed the current literature focused on the role of artificial intelligence (AI) for underserved populations and health equity in dermatology. Studies evaluating the utility and safety of AI model builds, and how they meet predefined bench...

Revolutionizing teledermatology: Exploring the integration of artificial intelligence, including Generative Pre-trained Transformer chatbots for artificial intelligence-driven anamnesis, diagnosis, and treatment plans.

Clinics in dermatology
The integration of teledermatology and artificial intelligence (AI) marks a significant advancement in dermatologic care. This study examines the synergistic interplay between these two domains, highlighting their collective impact on enhancing the a...

Is artificial intelligence useful in the practice of geriatric dermatology?

Clinics in dermatology
Geriatric dermatology has gained increasing importance through the years, alongside a steadily aging global population. Simultaneously, artificial intelligence (AI) technologies have become more advanced, and AI has been found to be useful in the gen...

Artificial intelligence in dermatopathology: Updates, strengths, and challenges.

Clinics in dermatology
Artificial intelligence (AI) has evolved to become a significant force in various domains, including medicine. We explore the role of AI in pathology, with a specific focus on dermatopathology and neoplastic dermatopathology. AI, encompassing machine...

Improving data participation for the development of artificial intelligence in dermatology.

Clinics in dermatology
Artificial intelligence (AI) has the potential to significantly impact many aspects of dermatology. The visual nature of dermatology lends itself to innovations in this space. The robustness of AI algorithms depends on the quality, quantity, and vari...

Human-multimodal deep learning collaboration in 'precise' diagnosis of lupus erythematosus subtypes and similar skin diseases.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Lupus erythematosus (LE) is a spectrum of autoimmune diseases. Due to the complexity of cutaneous LE (CLE), clinical skin image-based artificial intelligence is still experiencing difficulties in distinguishing subtypes of LE.

The Promises and Perils of Foundation Models in Dermatology.

The Journal of investigative dermatology
Foundation models (FM), which are large-scale artificial intelligence (AI) models that can complete a range of tasks, represent a paradigm shift in AI. These versatile models encompass large language models, vision-language models, and multimodal mod...