Dermatology

Comparison of volume- and surface-based magnetic resonance imaging morphometry algorithms in the detection of focal cortical dysplasia.

OBJECTIVE: Detection of focal cortical dysplasia (FCD) remains a major challenge in presurgical epilepsy diagnostics. Magnetic resonance imaging (MRI) morphometry increasingly improves lesion detection and postsurgical outcomes. The volume-based Morphometric Analysis Program, version 2018 (MAP18) with integrated artificial neural network and surface-based Multi-centre Epilepsy Lesion Detection (ME...

Limits of Artificial Intelligence Models for Skin Cancer Diagnosis in Realistic Settings.

IMPORTANCE: Artificial intelligence (AI) systems for skin cancer detection perform well in controlled settings but frequently underperform in everyday clinical practice, raising critical questions about their readiness for deployment. OBJECTIVE: To compare the diagnostic accuracy of AI algorithms vs human evaluators across varying expertise levels for skin lesion diagnosis, including rare and atyp...

Biomarker-driven and AI-assisted nanomedicine for breast cancer: advancing precision drug delivery from bench to bedside.

INTRODUCTION: Breast cancer remains the most prevalent malignancy among women worldwide, with its pronounced molecular heterogeneity demanding therape...

AI-based prediction of aspirin-exacerbated respiratory disease using nasal epithelial mRNA expression profiles.

BACKGROUND: Aspirin-exacerbated respiratory disease (AERD) is a distinct asthma endotype marked by asthma, nasal polyposis, and respiratory reactions ...

Magnetoelectric microrobots for spinal cord injury regeneration.

Spinal cord injury remains difficult to treat because of the intrinsically limited regenerative capacity of neurons. Although neural progenitor cell (...

Machine learning-based model for prediction of carbamazepine- and allopurinol-induced severe cutaneous adverse reactions in Vietnamese.

BACKGROUND: The low positive predictive value of HLA-B∗15:02 and HLA-B∗58:01 for risk stratification of carbamazepine (CBZ) and allopurinol (ALLO) ind...

Machine learning models of segmentation in acute ischemic stroke: a systematic review and meta-analysis.

BACKGROUND: Accurate segmentation of acute ischemic stroke (AIS) lesions on neuroimaging is essential for diagnosis, treatment decision-making, and pr...

Associations of serum per- and polyfluoroalkyl substances (PFAS) mixture with the risk of chronic diseases: evidence from single‑ , multi-pollutant, and machine learning models.

Per- and polyfluoroalkyl substances (PFAS) are persistent chemicals commonly found in consumer products. Despite growing concern over their health eff...

Deep learning-based neuroanatomical profiling reveals population-specific brain changes in multiple sclerosis: a large-scale Middle Eastern study.

BACKGROUND: Multiple sclerosis (MS) affects 2.8 million individuals worldwide, with Middle Eastern populations remaining underrepresented in neuroimag...

Identification of Polyamine Metabolism-Related Biomarkers in Psoriasis: A Study Based on Transcriptomics and Single-Cell Sequencing.

Psoriasis (PS) is linked to altered polyamine metabolism, which may drive chronic inflammation and abnormal keratinocyte proliferation. We integrated ...

Bridging Generations: Leveraging Technology and Artificial Intelligence for Better Research, Outreach, and Daily Practice.

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2025 annual meeting hosted a workshop entitled "Bridging generatio...

A bond-aware graph neural network integrated with docking, pharmacophore modeling and molecular dynamics for JAK2 inhibitors affinity prediction.

The Janus kinase (JAK)/STAT signaling pathway plays a pivotal role in cancer biology as well as in inflammatory and autoimmune disorders such as psori...

Frequency-Specific Alterations of Spontaneous Brain Activity in Stroke Patients with Upper Limb Motor Dysfunction: A Multi-Metric rs-fMRI and Machine Learning Study.

BACKGROUND: Post-stroke upper limb motor dysfunction is associated with complex alterations in brain function, but the frequency-specific characterist...

Vasoactive intestinal peptide associated 8-gene signature with prognostic and immune associations in melanoma.

Vasoactive intestinal peptide (VIP) plays a multifaceted role in cancer biology, yet its prognostic and immunological implications in melanoma remain ...

A comprehensive review of deep learning applications in the segmentation and classification of skin cancer.

Skin cancer (SC) is one of the most prevalent forms of cancer worldwide. Both melanoma and non-melanoma types pose major challenges for early detectio...

MSTM-Net: a two-stage prostate cancer segmentation network based on swin-transformer-mamba architecture.

BACKGROUND: Magnetic resonance imaging (MRI) has become a core imaging modality for prostate cancer screening and diagnosis. Accurate and automatic se...

KRT6A derived from mesenchymal stem cells as a potential biomarker and therapeutic target for alopecia areata: insights from multi-omics analysis and experimental evidence.

BACKGROUND: Mesenchymal stem cells (MSCs) secretome have shown promise in the treatment of alopecia areata (AA). However, the key therapeutic genes re...

ROI-guided virtual narrow band imaging for laryngeal cancer screening.

White light laryngoscopy is widely available but can miss subtle vascular changes associated with early laryngeal neoplasia. We developed a region-of-...

Deep Learning-Accelerated 3D FLAIR Enables Reliable MS Lesion Detection.

BACKGROUND AND PURPOSE: Deep learning-based reconstruction has the potential to shorten MRI acquisition while preserving diagnostic image quality, but...

Retinal lesion annotation on fundus imaging: an interobserver variability study.

Accurate detection and segmentation of retinal lesions in fundus photographs is essential for diagnosing diabetic retinopathy (DR) and for developing ...