Dermatology

The Role of Inflammatory Biomarkers in Disease Severity and Treatment Response across Psoriasis, Atopic Dermatitis, and Hidradenitis Suppurativa-A Narrative Review.

Chronic inflammatory skin diseases (CISDs) such as psoriasis (PsO), atopic dermatitis (AD), and hidradenitis suppurativa (HS) involve both cutaneous and systemic immune dysregulation, whereas commonly used scores rely largely on subjective clinical features and insufficiently reflect underlying inflammatory activity or cardiovascular risk. This review summarizes evidence across three biomarker dom...

Artificial Intelligence for Molecular Subtyping in Unresectable Gallbladder Cancer: A Proof-of-Concept Study for CT-based HER2 Status Prediction.

BACKGROUND/AIMS: Human epidermal growth factor receptor 2 (HER2) overexpression is a critical therapeutic target in gallbladder cancer (GBC), but detection requires invasive sampling. We developed a fully automated computed tomography (CT)-based framework to noninvasively predict HER2 status in unresectable GBC. METHODS: This single-center retrospective-prospective study included 213 pathologicall...

Physics-informed DynUNet for brain metastasis segmentation.

BACKGROUND: In neuro-oncology, detecting, segmenting, and delineating the boundaries of small-volume brain metastatic foci remains a significant chall...

The evolving PI-RADS paradigm.

Prostate MRI is central to the diagnostic pathway for prostate cancer (PCa), reducing unnecessary biopsies, improving the detection of clinically sign...

Automated periapical lesion segmentation and area-based PAI indexing: a comparative deep learning study on periapical radiographs.

BACKGROUND: Artificial intelligence can standardize periapical assessment, but few studies map pixel-level segmentation to clinically interpretable Pe...

Establishing Research Priorities for Artificial Intelligence Approaches in Dermatology Using an e-Delphi Exercise.

BACKGROUND: Artificial intelligence (AI) has significant potential to improve dermatological care, but most studies have concentrated on image-based s...

Single-cell profiling and machine learning identify cuproptosis-related fibroblast subpopulations and fibrogenesis modulator AEBP1 in endometriosis.

Endometriosis is characterized by progressive fibrosis and limited therapeutic options. Cuproptosis, a copper-dependent form of regulated cell death, ...

A longitudinal whole-body CT dataset with manually annotated tumor lesions.

We introduce Longitudinal-CT, a publicly available resource of whole-body computed tomography (CT) studies with exhaustive expert manual annotations o...

A robust stacked ensemble strategy with multi-optimizer CNN models for skin cancer classification.

Skin cancer is one of the most prevalent and potentially life-threatening cancers globally, making it a critical area of focus in medical research. Ea...

Comparing the Effectiveness of Artificial Intelligence Technology with 6th Year Dental Students for the Diagnosis of Inflammatory Bone Lesions of the Mandible in Panoramic Radiography.

This study aimed to evaluate the potential role of artificial intelligence (AI) as a diagnostic support tool for inexperienced clinicians by comparing...

A Landmark-Guided Dual-Stream Synergistic Framework for Automated Intracranial Aneurysm Detection in Magnetic Resonance Angiography.

Early and accurate detection of intracranial aneurysms (IAs) is critical for preventing rupture; however, manual interpretation of time-of-flight magn...

Quality over quantity: biopsy-anchored CT radiogenomics models outperform all-lesion training in a multi-tumour cohort despite a smaller sample size.

OBJECTIVE: Radiogenomics aims to non-invasively predict tumour genotypes from imaging, but most studies assume molecular homogeneity by assigning a si...

Quantification of edge-enhancing effects using accelerated deep learning reconstructed orbital MRI sequences.

RATIONALE AND OBJECTIVES: To qualitatively and quantitatively compare image quality, edge sharpness, and internal-structure delineation of accelerated...

Evaluating multi-task network architectures for simultaneous breast lesion segmentation and classification in ultrasound images.

Breast lesion segmentation and classification in ultrasound (US) images are two essential tasks for computer-aided diagnosis of breast cancer. However...

Transforming Psoriatic Disease Care Through Innovation and Real-World Data: GRAPPA 2025 Soapbox Highlights.

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2025 annual meeting, held in Bogotá, Colombia, featured soapbox pr...

Artificial intelligence with deep learning driven entropy-curvature attention mechanism for detection and segmentation of skin lesions using biomedical images.

In medical image analysis, skin lesion diagnosis remains a complicated task. Skin lesions are a prevalent form of skin disease that exists globally. A...

Machine-Learning-Based Prediction of Long-Term Efficacy of Nemolizumab: Post Hoc Analysis of Pooled Data from Two Phase III Clinical Trials.

INTRODUCTION: Nemolizumab is a humanized monoclonal antibody that specifically inhibits the receptor for interleukin-31, the major pruritogen in atopi...

Efficacy of short-course bevacizumab for brain tumor radiation necrosis with a volumetric analysis.

PURPOSE: Radiation necrosis (RN) is a challenging complication of cranial irradiation, often requiring corticosteroids for management. This study eval...

Mitigating hallucinations in synthesized clinical texts to improve multimodal deep learning for dermatology.

OBJECTIVE: Despite recent advancements in the development of foundation models and multimodal (MM) architectures in dermatology, their translation to ...

Classification of occlusal caries severity using spectrophotometric CIELAB measurements and machine learning algorithms.

OBJECTIVES: This study evaluated whether spectrophotometric CIELAB color measurements can support machine-learning (ML) classification of occlusal car...