AI Medical Compendium Journal:
JAMA dermatology

Showing 11 to 20 of 20 articles

Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening: A Qualitative Study.

JAMA dermatology
IMPORTANCE: The use of artificial intelligence (AI) is expanding throughout the field of medicine. In dermatology, researchers are evaluating the potential for direct-to-patient and clinician decision-support AI tools to classify skin lesions. Althou...

Keratinocytic Skin Cancer Detection on the Face Using Region-Based Convolutional Neural Network.

JAMA dermatology
IMPORTANCE: Detection of cutaneous cancer on the face using deep-learning algorithms has been challenging because various anatomic structures create curves and shades that confuse the algorithm and can potentially lead to false-positive results.

Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks.

JAMA dermatology
IMPORTANCE: Convolutional neural networks (CNNs) achieve expert-level accuracy in the diagnosis of pigmented melanocytic lesions. However, the most common types of skin cancer are nonpigmented and nonmelanocytic, and are more difficult to diagnose.

Population-Based Analysis of Histologically Confirmed Melanocytic Proliferations Using Natural Language Processing.

JAMA dermatology
IMPORTANCE: Population-based information on the distribution of histologic diagnoses associated with skin biopsies is unknown. Electronic medical records (EMRs) enable automated extraction of pathology report data to improve our epidemiologic underst...