Dermatology

Integrating Artificial Intelligence-Based Mentorship Tools in Dermatology.

Artificial intelligence in dermatology: GPT-3.5-Turbo demonstrates strengths and limitations in residency exams.

Advancing dermatology education with AI-generated images.

Enhancing skin lesion classification with advanced deep learning ensemble models: a path towards accurate medical diagnostics.

Skin cancer, including the highly lethal malignant melanoma, poses a significant global health chall...

Automatic thoracic aorta calcium quantification using deep learning in non-contrast ECG-gated CT images.

Thoracic aorta calcium (TAC) can be assessed from cardiac computed tomography (CT) studies to improv...

Analysis of Dermatology Journal Policy Toward Artificial Intelligence.

MRI-Based Machine Learning Radiomics for Preoperative Assessment of Human Epidermal Growth Factor Receptor 2 Status in Urothelial Bladder Carcinoma.

BACKGROUND: The human epidermal growth factor receptor 2 (HER2) has recently emerged as hotspot in t...

Machine Learning Applications in Psoriasis Treatment: A Systematic Review.

Artificial intelligence in dermatology: advancements and challenges in skin of color.

Artificial intelligence (AI) uses algorithms and large language models in computers to simulate huma...

Applications of Machine Learning on Alopecia Areata: A Systematic Review.

The Promises and Perils of Foundation Models in Dermatology.

Foundation models (FM), which are large-scale artificial intelligence (AI) models that can complete ...

Echoes of images: multi-loss network for image retrieval in vision transformers.

This paper introduces a novel approach to enhance content-based image retrieval, validated on two be...

Combining artificial intelligence and human expertise for more accurate dermoscopic melanoma diagnosis: A 2-session retrospective reader study.

Impact of direct use of artificial intelligence algorithms on patient autonomy in dermatology.

Minimum labelling requirements for dermatology artificial intelligence-based Software as Medical Device (SaMD): A consensus statement.

BACKGROUND/OBJECTIVES: Artificial intelligence (AI) holds remarkable potential to improve care deliv...

Lesion segmentation using 3D scan and deep learning for the evaluation of facial portwine stain birthmarks.

BACKGROUND: Portwine stain (PWS) birthmarks are congenital vascular malformations. The quantificatio...

Deep Learning Combined with Radiologist's Intervention Achieves Accurate Segmentation of Hepatocellular Carcinoma in Dual-Phase Magnetic Resonance Images.

PURPOSE: Segmentation of hepatocellular carcinoma (HCC) is crucial; however, manual segmentation is ...

Patient and dermatologists' perspectives on augmented intelligence for melanoma screening: A prospective study.

BACKGROUND: Artificial intelligence (AI) shows promising potential to enhance human decision-making ...

Automated Machine Learning versus Expert-Designed Models in Ocular Toxoplasmosis: Detection and Lesion Localization Using Fundus Images.

PURPOSE: Automated machine learning (AutoML) allows clinicians without coding experience to build th...

Residual facial erythema in atopic dermatitis patients treated with dupilumab stratified by machine learning.

BACKGROUND: Persistent facial erythema represents a significant complication in atopic dermatitis (A...

LAMA: Lesion-Aware Mixup Augmentation for Skin Lesion Segmentation.

Deep learning can exceed dermatologists' diagnostic accuracy in experimental image environments. How...