Dermatology

Single-Stage Lesion Identification in $^{68}$Ga-DOTATATE PET Images.

OBJECTIVE: Positron emission tomography (PET) is a commonly used imaging modality for assessment of neuroendocrine tumors (NETs), and lesion identification in PET images is a key step in the development of effective treatments. Deep neural networks have recently produced encouraging performance of automated lesion identification with PET imaging. However, most methods require a predefined region/v...

A Comparative Evaluation of 7T MRI for Epilepsy with Deep-Learning-Based Image Reconstruction and Dynamic Parallel Transmission.

OBJECTIVES: 7T MRI enhances lesion detection in epilepsy but is limited by radiofrequency transmission field (B1+) inhomogeneity and long scan times. Recent advancements in dynamic parallel transmission and deep-learning-based reconstructions offer promising solutions. We aimed to optimize an enhanced 7T epilepsy protocol incorporating these innovations and evaluate real-world benefits compared to...

Integrated LIBS-Raman spectroscopy coupled with explainable machine learning for biochemical characterization of melanoma.

Melanoma remains one of the most aggressive and lethal cutaneous malignancies, underscoring the need for objective and label-free diagnostic methods t...

Lesion network mapping in pediatric epilepsy.

OBJECTIVE: To describe the current use, limitations, and future directions of lesion network mapping in pediatric epilepsy. METHODS: Narrative review ...

High-Resolution MRI Using Artificial Intelligence-Assisted Acceleration and Radial Dynamic Contrast Enhancement for Improved Detection of Pituitary Microadenomas in Cushing's Disease.

BACKGROUND AND PURPOSE: Accurate detection of pituitary microadenomas is critical for the diagnosis and treatment of Cushing's disease (CD). However, ...

Machine learning-driven computational drug repurposing to identify new tubulin inhibitors against cancer.

Tubulin is a validated anticancer target, yet the clinical translation of colchicine-binding site inhibitors remains limited by toxicity and resistanc...

Integrating multi-source data and machine learning to Decipher the psoriasis-COPD comorbidity.

Hybrid vision transformer and graph neural network model with region-adaptive attention for enhanced skin cancer prediction.

A well-known and potentially lethal skin cancer requires prompt detection and diagnosis. Complex spatial linkages and global contextual information in...

Low resource federated learning for classification of nail disease by deploying cross-silo and heterogeneously dataset distributions.

Nail diseases, including such common conditions as fungus, and more serious issues like melanoma, may be important clues to the overall health and req...

DermaGPT a federated multimodal framework with a meta learned trust function for interpretable dermatology diagnostics.

Advances in generative and federated artificial intelligence enable privacy-aware diagnostic systems that integrate multimodal reasoning and explainab...

Multi-omics profiling of chronic immune-mediated skin diseases: SKINERGY protocol and strategic evaluation.

BACKGROUND: The Dutch flagship project Next Generation ImmunoDermatology (NGID) aims to profile five chronic immune-mediated inflammatory skin disease...

A hybrid approach for accurate skin lesion segmentation using LEDNet and Swin-UMamba.

Accurate delineation of skin lesions in images is important for skin cancer detection. Existing methods often struggle with inherent complexities, suc...

Network for Real-time Laryngeal Lesions Video Object Detection.

Early and accurate diagnosis of nasopharyngeal-laryngeal tumors is critical for improving patient prognosis. Deep learning methods have achieved signi...

TrkA abundance is increased in cutaneous nerves in bortezomib-induced neuropathy.

Tropomyosin receptor kinase A (TrkA), a high-affinity receptor for nerve growth factor (NGF), is implicated in nociception and local angiogenesis. We ...

Comprehensive segmentation of focal cortical dysplasia by combining surface-based and whole-brain MRI deep learning algorithms: a proof-of-concept study.

Introduction.Focal cortical dysplasia type II (FCD II) is a significant cause of drug-resistant epilepsy, and the full surgical resection of the lesio...

Enhancing nail disease diagnosis: a capsule network with SE attention and dual backbone models.

Nail diseases, including fungal infections and malignancies, pose significant health risks and may lead to severe complications if not accurately diag...

Identification of common genes and biomarkers between Dermatomyositis and rheumatoid arthritis through integrated bioinformatics.

BACKGROUND: Dermatomyositis (DM) and rheumatoid arthritis (RA) share immuno-inflammatory features, yet mechanisms underlying their comorbidity remain ...

Phenotyping of Patients with Age-Related Macular Degeneration Using Artificial Intelligence-Driven Biomarker Patterns in OCT.

PURPOSE: To leverage artificial intelligence-based OCT analysis to classify age-related macular degeneration (AMD) images into distinct subgroups base...

Applications of the Non-invasive Skin Imaging Techniques and Image-based Artificial Intelligence in Rosacea: A Narrative Review.

BACKGROUND: Rosacea is a common chronic inflammatory dermatosis with complex pathophysiology and heterogeneous clinical manifestations. Despite its pr...

A rapid and accurate guanidine CEST imaging in ischemic stroke using a machine learning approach.

OBJECTIVE: Rapid and accurate mapping of brain tissue pH is crucial for early diagnosis and management of ischemic stroke. Amide proton transfer (APT)...