Dermatology

Artificial Intelligence applied to surgical pathology in the management of cutaneous melanoma.

Surgical pathology remains the cornerstone for the diagnosis, staging and prognostic stratification ...

Portable Deep Learning-Assisted Device for Automated Interincisal Opening Assessment and Oral Submucous Fibrosis Lesion Identification: A Translational Clinical Study.

Oral submucous fibrosis (OSMF) is a chronic, progressive, potentially malignant disorder prevalent i...

Discovery of Epidermal Growth Factor-Like 7 as a Potential Non-Invasive Biomarker for Fibrosis and Mortality Risk in MASLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major cause of liver-related m...

Melanoma in Skin of Color: Diagnostic Challenges, Overdiagnosis, and Emerging Tools.

Melanoma in skin of color (SOC), defined as Fitzpatrick skin tones IV-VI, presents unique epidemiolo...

Melanoma Prognostication Using AI-Guided Histopathology.

Accurate diagnosis and risk stratification are central for optimal management of patients with melan...

AI Dermatology's Unfulfilled Promise: Why Early Melanoma Detection Remains Unverified.

A growing number of artificial intelligence (AI) systems for melanoma diagnosis now match dermatolog...

Construction of risk prediction models for psoriasis based on 45 dietary nutrients using machine learning and SHAP analysis.

BACKGROUND AND OBJECTIVES: To develop and validate a machine learning model to predict the risk of p...

Implementation of Total Body Photography for Skin Cancer Early Detection: A Systematic Review.

Advances in imaging technologies, such as total body photography (TBP), and the increasing capabilit...

Current and Emerging Drug Therapy for Acne Vulgaris: A Comprehensive Review.

Acne vulgaris is a highly prevalent chronic inflammatory disorder of the pilosebaceous unit that aff...

Missed Diagnosis of Clear Cell Renal Cell Carcinoma on Noncontrast Computed Tomography: The Potential Role of Artificial Intelligence in Reducing Radiological Diagnostic Error.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common histological subtype of malig...

MRI Characteristics of Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease: A Review.

IMPORTANCE: Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a demyelinati...

Comment on "Plasma metabolomics combined with machine learning for postoperative prognostic stratification in hormone receptor-positive/human epidermal growth factor receptor 2-negative early breast cancer".

AI Clinical Trials Registered on ClinicalTrials.gov Showed Persistent Misalignment with Global Disease Burden, 2010-2026.

OBJECTIVE: To determine whether artificial intelligence (AI) clinical trial activity aligns with glo...

A Progression-Associated Tumor-Reactive T-Cell Signature Predicts Immunotherapy Response and Reveals ICOS-High CD8 T-Cell Functional States in Head and Neck Squamous Cell Carcinoma.

Immune checkpoint blockade has improved outcomes for patients with head and neck squamous cell carci...

Evaluation of the detection accuracy of a fully automated AI-based lesion segmentation tool in whole-body FDG PET/CT for lymphoma.

BACKGROUND: This study evaluated an AI-based lesion segmentation tool using a hybrid 2D-3D deep lear...

Multicentre evaluation of artificial intelligence risk classification for detection of clinically significant prostate cancer on biparametric MRI.

OBJECTIVES: To compare a commercially available artificial intelligence (AI) risk-classification sys...

"Acne in the Age of ChatGPT": an artificial intelligence-generated and evidence-based continuing medical education distance course for Italian physicians.

The AI-CHECK (Artificial Intelligence for CME Health E-learning Contents and Knowledge) study aimed ...

Mapping the potential occurrence of Cutaneous Leishmaniasis using machine learning algorithms and remote sensing data.

Cutaneous Leishmaniasis (CL) is a vector-borne parasitic disease closely linked to environmental con...

Reply - Letter to the Editor: Comment on "Plasma metabolomics combined with machine learning for postoperative prognostic stratification in hormone receptor-positive/human epidermal growth factor receptor 2-negative early breast cancer".

Andrographolide suppresses triple-negative breast cancer proliferation through the p53/CDK1 axis: a multiscale analysis combining network pharmacology and machine learning.

Triple-negative breast cancer (TNBC), a highly aggressive molecular subtype characterized by a lack ...

Predicting relapse in pediatric IgA vasculitis in the era of machine learning: an explainable hybrid ensemble model.

OBJECTIVES: This study aimed to develop an explainable hybrid ensemble machine learning (ML) model t...