AI Medical Compendium Topic

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Skin Diseases

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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...

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...

Deep learning-assisted multispectral imaging for early screening of skin diseases.

Photodiagnosis and photodynamic therapy
INTRODUCTION: Melanocytic nevi (MN), warts, seborrheic keratoses (SK), and psoriasis are four common types of skin surface lesions that typically require dermatoscopic examination for definitive diagnosis in clinical dermatology settings. This proces...

Interpretable machine learning for dermatological disease detection: Bridging the gap between accuracy and explainability.

Computers in biology and medicine
Research on disease detection by leveraging machine learning techniques has been under significant focus. The use of machine learning techniques is important to detect critical diseases promptly and provide the appropriate treatment. Disease detectio...

ChatGPT and dermatology.

Italian journal of dermatology and venereology
Since the development of the artificial intelligence (AI), several applications have been proposed. Among these, the intersection of AI and medicine has sparked a wave of innovation, revolutionizing various aspects of healthcare delivery, diagnosis, ...

Generative artificial intelligence in dermatology: Recommendations for future studies evaluating the clinical knowledge of models.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)

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...