AIMC Topic: Dermatologists

Clear Filters Showing 41 to 50 of 58 articles

Deep-learning-based, computer-aided classifier developed with a small dataset of clinical images surpasses board-certified dermatologists in skin tumour diagnosis.

The British journal of dermatology
BACKGROUND: Application of deep-learning technology to skin cancer classification can potentially improve the sensitivity and specificity of skin cancer screening, but the number of training images required for such a system is thought to be extremel...

Dermatologist-level classification of skin cancer with deep neural networks.

Nature
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of ski...

Early diagnosis model of mycosis fungoides and five inflammatory skin diseases based on a multimodal data-based convolutional neural network.

The British journal of dermatology
BACKGROUND: Mycosis fungoides (MF) is the most common type of cutaneous T-cell lymphoma, and early-stage MF is difficult to differentiate from erythematous inflammatory disease. With the exception of biopsy, noninvasive information such as a patient'...

Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study.

Nature communications
Artificial intelligence (AI) systems substantially improve dermatologists' diagnostic accuracy for melanoma, with explainable AI (XAI) systems further enhancing their confidence and trust in AI-driven decisions. Despite these advancements, there rema...

Mobile health apps for skin cancer triage in the general population: a qualitative study on healthcare providers' perspectives.

BMC cancer
BACKGROUND: Mobile health (mHealth) applications (apps) integrated with artificial intelligence for skin cancer triage are increasingly available to the general public. Nevertheless, their actual uptake is limited. Although endorsement by healthcare ...

Physician Opinions on Artificial Intelligence Chatbots In Dermatology: A National Online Cross-Sectional Survey of Dermatologists.

Journal of drugs in dermatology : JDD
BACKGROUND: Artificial intelligence chatbots (AIC) have sharply risen in popularity. Dermatology, heavily involving visual, clinical, and pathological pattern-recognition techniques, will be impacted by AIC. Thus, this study aims to categorize the at...

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

Clinical and experimental dermatology
BACKGROUND: ChatGPT is an online language-based platform designed to answer questions in a human-like way, using deep learning -technology.

Unveiling the power of convolutional neural networks in melanoma diagnosis.

European journal of dermatology : EJD
Convolutional neural networks are a type of deep learning algorithm. They are mostly applied in visual recognition and can be used for the identification of melanomas. Multiple studies have evaluated the performance of convolutional neural networks, ...