Dermatology

Evaluation of the clinical applicability of artificial intelligence in determining systemic therapy indications and treatment selection in psoriasis.

OBJECTIVE: To evaluate the concordance between artificial intelligence (AI)-recommended and dermatologist-selected treatments in real-world psoriasis care. METHODS: Eighty-two patients with psoriasis were included in this study. An AI model (ChatGPT) was provided along with treatment guidelines and clinical trial data to generate treatment recommendations. The concordance was assessed for systemic...

Deep Learning for Automated Quantification and Differential Diagnosis of Cutaneous Mastocytoma on Dynamic Ultrasound.

Predicting Age-Related Facial Hyperpigmentation via Dermatologist Knowledge Elicitation and Generative Modeling.

INTRODUCTION: Facial hyperpigmentation is a primary marker of skin aging in Asian populations. While many artificial intelligence (AI)-based aging sim...

Quantitative Assessment of Nanoplastic Toxicity Risks Across Aquatic Trophic Levels with Data-Driven Models and Exposure Experiments.

Emerging contaminants such as nanoplastics (NPs) pose significant risks to aquatic ecosystems. However, the key features governing NPs toxicity and th...

Optimising biologic therapy in psoriasis: dose adjustment, treatment duration, and tapering-an expert perspective.

INTRODUCTION: Biologic therapies have transformed the management of moderate-to-severe psoriasis; however, long-term treatment requires optimization s...

Standardizing PSMA PET/CT reporting in prostate cancer: from structured frameworks to AI-assisted interpretation.

PSMA PET/CT is increasingly used for prostate cancer staging, restaging, treatment selection, and therapy response assessment. In parallel, several in...

From diagnostic labels to radiology reports: a unified multi-modal framework for lesion detection and segmentation.

Deep learning-based vision models are playing an increasingly pivotal role in clinical diagnosis and treatment.However, existing approaches predominan...

Combination of color-Doppler ultrasound and MRI to improve lacrimal gland lesion characterization: A machine learning approach.

PURPOSE: The purpose of this study was to develop a machine learning-based algorithm based on a combination of magnetic resonance imaging (MRI) and co...

Exploring the immune landscape and immunotherapy relevance of ER stress-related lncRNAs in melanoma through multi-omics and explainable machine learning.

BACKGROUND: Melanoma is a highly aggressive malignancy with poor clinical outcomes, and endoplasmic reticulum (ER) stress plays an important role in t...

Attention guided fair artificial intelligence modeling for skin cancer diagnosis.

Artificial intelligence (AI) has shown promise in dermatology, offering accurate and non-invasive diagnosis of skin cancer. While extensive research h...

Data-driven system identification in cancer systems biology: A multiscale modeling approach to melanoma.

BACKGROUND AND OBJECTIVE: Developing systems biology models of cancer is critical for improving understanding of complex biological interactions and a...

Prognostic prediction models for psoriatic arthritis in psoriasis: A systematic review.

BACKGROUND: Psoriatic arthritis is a chronic inflammatory arthropathy that affects up to 22% of individuals with psoriasis. Identifying patients at hi...

Integrated bioinformatics and machine learning for shared diagnostic genes and mechanisms between periodontitis and psoriasis.

BACKGROUND: Periodontitis and psoriasis are two prevalent conditions that are bidirectionally associated. However, the molecular basis remains poorly ...

AI-Driven Decision Thresholds in Cariology: A Systematic Review of Lesion Stage Detection on Bitewing Radiographs.

INTRODUCTION: This systematic review evaluates the stage-specific diagnostic accuracy of artificial intelligence (AI) models for caries detection and ...

A recyclable, mechanically robust, and anti-freezing chitosan/polyvinyl alcohol/polyaniline conductive hydrogel for multifunctional sensing application.

Conductive hydrogels have demonstrated fascinating application potential in flexible electronics. However, conductive hydrogels often exhibit poor mec...

Deep Learning vs. Traditional Machine Learning in the Diagnosis of Cutaneous Drug Eruptions: A Comparative Study with Explainable AI on Whole-Slide Images.

Histopathological diagnosis of cutaneous drug eruptions (CDEs) presents a challenge in dermatopathology due to morphological overlap and high inter-ob...

Identifying breast cancer subtypes and exploring spatial expression patterns of the key subtype-specific gene based on pathological images, single-cell sequencing, and spatial transcriptomic data.

BACKGROUND: Breast cancer (BRCA) is a heterogeneous disease. Accurate prognosis and molecular subtypes are critical for personalized treatment in BRCA...

Adaptive distribution-aware transformer for multi-scale visual representation learning on imbalanced and low-resolution data.

Deep learning models often struggle with class imbalance and low-resolution medical images, where critical spatial details and minority-class features...

Deep Learning Assisted Double Inversion Recovery improves Focal Lesion Detection in Optic Neuropathy.

OBJECTIVES: To compare the acquisition time, image quality, and diagnostic confidence of DL-accelerated DIR (DIR-DL) with conventional MRI in patients...

Ultrasonographic Phenotypes and Segmentation Model Comparison for Primary Breast Lesions and Axillary Lymph Nodes in Triple-negative Breast Cancer.

RATIONALE AND OBJECTIVES: To describe clinicopathologic and ultrasonographic heterogeneity across immunohistochemistry-based FUSCC surrogate subtypes ...