Dermatology

Multimodal Large Language Models Versus Dermatologists for Smartphone-Image Classification of Suspicious Cutaneous Lesions: A Diagnostic Accuracy Study.

Machine learning models identify prognostic factors in systemic lupus erythematosus patients with epstein-barr virus infection.

OBJECTIVE: To identify poor prognostic factors in Epstein-Barr virus (EBV)-positive systemic lupus erythematosus (SLE) using interpretable machine-learning (ML) models. METHOD: We retrospectively analysed 217 EBV-positive SLE in-patients (2018-2022). Clinical and laboratory variables were compared between favorable and poor prognosis groups. Seven ML algorithms-logistic regression, support vector ...

Lesion-Level Association Between Artificial Intelligence-Derived Coronary Calcium Volume and Plaque Vulnerability.

BACKGROUND: Extensively calcified lesions are typically at low risk for lesion-level acute events, which may be related to less vulnerable plaques. OB...

Clinical evaluation of deep learning-accelerated 3D FLAIR imaging at 1.5T and 3T for visualization of cerebral white matter lesions.

BackgroundFluid-attenuated inversion recovery (FLAIR) imaging is a standard sequence used for the detection of white matter lesions; however, 1-mm iso...

Patient Acceptability, Perceptions and Concerns Regarding Artificial Intelligence Scribes in Outpatient Dermatology Clinics.

This cross-sectional survey assessed patient acceptability, perceptions and concerns regarding ambient artificial intelligence (AI) scribes in an outp...

Retinal Pigment Epithelium and Microglia Transplantation in Age-related Macular Degeneration.

Age-related macular degeneration (AMD) remains a leading cause of irreversible blindness worldwide, characterized by the progressive breakdown of the ...

Integrating network pharmacology, machine learning, and molecular docking to explore the therapeutic mechanisms of Huangqin in atopic dermatitis: A STROBE-compliant observational study.

Atopic dermatitis (AD) is a chronic inflammatory skin disorder with complex pathogenesis, and current therapies face limitations in efficacy and safet...

COLLECT: A Counterfactual Oral Lesion Library for Trustworthy AI Evaluation.

Intraoral mucosal lesions are difficult to diagnose because they vary widely in appearance and cause. Deep-learning models perform well for oral lesio...

AI-assisted diagnosis of nail unit melanoma and melanonychia using a clinical deep learning model.

BACKGROUND AND OBJECTIVES: Nail unit melanoma (NUM) is a rare but potentially fatal malignancy often misdiagnosed as melanonychia. Because biopsy may ...

Clinically Interpretable Deep Learning for Differentiating Vitiligo and Postinflammatory Hypopigmentation: Diagnostic Accuracy Study.

BACKGROUND: Distinguishing vitiligo from postinflammatory hypopigmentation (PIH) is clinically challenging because both conditions may present with si...

Development and validation of an interpretable machine learning model for predicting hypertension risk in patients with psoriasis.

OBJECTIVE: Hypertension is a common yet frequently underdiagnosed comorbidity in psoriasis patients. Early identification and blood pressure control a...

Comparison between physician assessment and artificial intelligence analysis in digital dermoscopy: evaluation of 71 dermoscopic cases.

Artificial intelligence (AI)-based dermoscopic analysis is increasingly being used to assist dermatologists in the early detection and monitoring of p...

Large-Scale Plasma Proteomics Profiles for Predicting Atrial Fibrillation Associated Stroke Risk : Type of manuscript: Original Research.

BACKGROUND: Stroke is a major complication of atrial fibrillation (AF), and risk prediction using the congestive heart failure, hypertension, age, dia...

Assessing Alopecia Areata Misinformation: Social Media Analysis.

BACKGROUND: Alopecia areata (AA) is an autoimmune, hair loss-inducing disease affecting individuals of all genders and ethnic backgrounds worldwide. A...

A large-scale comparative study of YOLO-based detectors for ischemic stroke lesion localization on diffusion-weighted imaging.

Ischemic stroke lesion localization on diffusion-weighted imaging (DWI) remains challenging because acute lesions may be small, faint, irregular, or m...

Deep learning-based assessment of HER2-ultralow expression in breast cancer: a multi-center validation study across primary and metastatic lesions.

Accurate assessment of human epidermal growth factor receptor 2 (HER2) expression is foundational for targeted therapy in breast cancer (BC). The rece...

Personalized cancer vaccines: bridging immune-oncology and precision medicine for advanced therapeutics.

Despite advancements in therapeutic cancer vaccines, clinical translation has been hindered by limited efficacy, with Sipuleucel-T remaining the only ...

Preoperative PET/CT phenotype of gastric-type endocervical adenocarcinoma: integrated morphological, metabolic, serological, and explainable machine-learning analysis.

PURPOSE: Gastric-type endocervical adenocarcinoma (GAS) is an aggressive, non-HPV-associated cervical adenocarcinoma that is often difficult to recogn...

Who Writes the Note: The Training Data Behind Artificial Intelligence Scribes in Dermatology.

AI scribes are increasingly used to reduce clinical documentation burden, but ethical evaluation must extend beyond efficiency to include training, go...

Current research landscape and future prospects of in silico modeling approaches for atopic dermatitis.

Atopic dermatitis (AD) is a chronic, multifactorial inflammatory skin disease with a complex, heterogeneous pathogenesis. Understanding its mechanisms...