Dermatology

Visual In-Context Learning for Few-Shot Eczema Segmentation.

Automated diagnosis of eczema from digital camera images is crucial for applications that allow pati...

Channel Fitting Network for Retinal Lesion Segmentation from OCT Images.

Retinal lesion is a cause of age-related macular degeneration that poses a big threat to elderly pop...

Enhancing Choroidal Nevus Position Identification through CNN-Based Segmentation of Eye Fundus Images.

Diagnosing choroidal nevus in color fundus images is challenging for clinicians not regularly practi...

Lesion Segmentation in Skin Cancer Images using Fusion Model via Deep Learning Networks.

Skin cancer, one of the most prevalent and life-threatening cancers globally, has become a focus of ...

Unravelling tumour cell diversity and prognostic signatures in cutaneous melanoma through machine learning analysis.

Melanoma, a highly malignant tumour, presents significant challenges due to its cellular heterogenei...

Screening Outcomes of Mammography with AI in Dense Breasts: A Comparative Study with Supplemental Screening US.

Background Comparative performance between artificial intelligence (AI) and breast US for women with...

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

Enhancing diagnostic precision in liver lesion analysis using a deep learning-based system: opportunities and challenges.

Widening the scope of artificial intelligence applications in dermatology.

Comparing the quality of ChatGPT- and physician-generated responses to patients' dermatology questions in the electronic medical record.

BACKGROUND: ChatGPT is a free artificial intelligence (AI)-based natural language processing tool th...

Artificial intelligence-generated patient information leaflets: a comparison of contents according to British Association of Dermatologists standards.

BACKGROUND: Patient information leaflets (PILs) can supplement a clinical consultation and provide a...

Ethical and legal considerations for the use of artificial intelligence in global health dermatology.

Evaluation of dermatological conditions: the diagnostic potential of artificial intelligence in primary care.

Classifying real-world macroscopic images in the primary-secondary care interface using transfer learning: implications for development of artificial intelligence solutions using nondermoscopic images.

BACKGROUND: The application of deep learning (DL) to diagnostic dermatology has been the subject of ...

ChatGPT versus clinician: challenging the diagnostic capabilities of artificial intelligence in dermatology.

BACKGROUND: ChatGPT is an online language-based platform designed to answer questions in a human-lik...

Performance of large language model artificial intelligence on dermatology board exam questions.

Revolutionizing dermatology residency: artificial intelligence for knowledge and clinical milestones assessment.

Advancing dermatology: artificial intelligence-based solutions to reducing the risk of misdiagnosis.

Advancing dermatology: embracing the power of artificial intelligence. Comment on 'Artificial intelligence-assisted publishing in five prominent dermatology journals: a quantitative study of recent publications'.

Artificial intelligence-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma.

BACKGROUND: Risk stratification of cutaneous squamous cell carcinoma (cSCC) is essential for managin...

Artificial intelligence-assisted publishing in five prominent dermatology journals: a quantitative study of recent publications.