Dermatology

Identification of clinical phenotypes and disease trajectories in SLE using AI through a natural language processing framework.

OBJECTIVES: Electronic Health Records (EHRs) contain a wealth of unstructured patient data that can be leveraged using Artificial Intelligence (AI). This study aimed to develop a Natural Language Processing (NLP)pipeline to identify clinical phenotypes and disease trajectories in patients with Systemic Lupus Erythematosus (SLE) from EHRs. METHODS: EHR data from SLE patients were included. A standa...

The 487-gene expression profile test guides systemic therapy selection to improve outcomes for patients with atopic dermatitis: Results from a prospective trial.

BACKGROUND: Current atopic dermatitis (AD) therapy selection does not account for molecular drivers of disease, contributing to inadequate disease control for half of patients. OBJECTIVE: Develop and validate a gene expression profile (GEP) test to guide AD systemic therapy selection. METHODS: In a prospective study, AD or psoriasis lesion skin scrapings were analyzed by RNA-Seq, and treatments an...

CanSig Benchmarks Methods for Reproducible Cancer Cell State Discovery from Single-Cell Transcriptomic Data.

UNLABELLED: Single-cell RNA sequencing facilitates the discovery of gene expression signatures that define cell states across patients, which could be...

Kaposi's sarcoma in individuals living with HIV: comparative assessment of AI-based clinical responses using a standardized questionnaire set.

OBJECTIVE: To comparatively evaluate the clinical responses of three digital platforms (ChatGPT 5.2, DeepSeek, Consensus) in terms of responsiveness, ...

Bioinspired Cold-Laminated Ultrathin Hydrogels as a Broadly Adaptive Platform for Physiological Monitoring.

Soft bioelectronics provide a powerful platform for physiological monitoring, yet conventional hydrogel-based devices are constrained by inherent trad...

Deep learning for histopathological diagnosis of esophageal squamous cell carcinoma in biopsies: A multicenter analysis.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a major cause of cancer mortality in Asia, where histopathological diagnosis of endoscopic bi...

Late distant recurrence prediction model in premenopausal women with ER-positive/HER 2-negative breast cancer: A multicenter retrospective study.

BACKGROUND: Late distant recurrence (DR) remains a significant challenge in estrogen receptor (ER)-positive/Human Epidermal Growth Factor Receptor 2 (...

Class-balanced dermoscopic lesion segmentation using MoG-LISA and optimized Swin-UNet via the GM-FDE framework.

Automatic skin lesion segmentation is one of the key pivotal tasks in dermatological image processing, with important consequences in early melanoma d...

artificial intelligence-enabled precision medicine for inflammatory skin diseases.

Recent advances in artificial intelligence (AI) and multimodal data collection are revolutionizing dermatology. Generative AI and machine-learning app...

Reinforcement learning-guided segment anything model for MRI prostate and dominant intraprostatic lesions auto-segmentation.

Objective. Accurate segmentation of the prostate and dominant intraprostatic lesions (DILs) on magnetic resonance imaging (MRI) is important for prost...

Diagnostic model and identification of IGFBP2 as an aging-related biomarker and therapeutic target for systemic sclerosis-associated interstitial lung disease through integrated bioinformatics and machine learning approaches.

BACKGROUND: Cellular senescence is a critical contributor to the pathogenesis of systemic sclerosis-associated interstitial lung disease (SSc-ILD). Ho...

Facial Botox Injection Point Detection Using YOLOv8 Enhanced with CBAM and BiFPN: A Multi-Perspective Deep Learning Approach.

Botox is one of the most frequently performed procedures in cosmetic dermatology, aimed at reducing wrinkles and enhancing facial aesthetics. However,...

Automated segmentation of pterygium lesions using multiscale deep learning networks.

Pterygium is an eye condition that needs to be identified at an early stage so that its progression can be mitigated in order to avoid the possible th...

Comparison of an AI-based prognostic assay with gene expression profiling in early-stage melanoma.

Multicentre development and validation of data-driven claims-based algorithms for identifying dermatomyositis and polymyositis in Japan.

OBJECTIVE: To develop and validate data-driven algorithms for identifying patients with dermatomyositis (DM) and polymyositis (PM) using Japanese admi...

Quantum-enhanced multimodal prognostic transformer for skin disease progression prediction and visualization.

Accurate classification and staging of skin diseases such as monkeypox, chickenpox, and measles are critical for timely clinical intervention, particu...

A novel deep learning model for automated diagnosis of oral squamous cell carcinoma and related leukoplakia in pathological images.

BACKGROUND: Oral squamous cell carcinoma (OSCC) is the sixth most common type of cancer worldwide. Its diagnosis and treatment rely on pathological se...

Efficacy of artificial intelligence-assisted upper gastrointestinal endoscopy for neoplasm detection: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND AND AIMS: EGD remains the primary diagnostic modality for evaluating lesions of the upper gastrointestinal (UGI) tract. This meta-analysis ...

Characterization of cutaneous wound healing in swine.

The porcine excisional wound model is widely regarded as the most translationally relevant preclinical platform for studying human skin wound healing ...

Atopic Dermatitis in Denmark: Regional Variation.

Using national registers, this study investigates regional variations in the number of individuals with and treatment of atopic dermatitis (AD) in Den...