Dermatology

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 cr...

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-accelera...

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 im...

A web-based semi-supervised deep learning platform for automated AS-OCT assessment and monitoring of infectious keratitis.

Infectious keratitis (IK) is a leading cause of corneal blindness globally. Accurate severity assess...

Predicting early-stage breast cancer disease-free survival and adjuvant therapy benefit from multimodal information using deep learning.

Accurate prediction of disease-free survival (DFS) is essential for tailoring adjuvant regimens and ...

Radiomics using contrast-enhanced T1-weighted imaging and clinical features for predicting response to EGFR-TKIs in EGFR-mutated non-small cell lung cancer patients with brain metastases.

OBJECTIVES: To construct and validate a model based on clinical characteristics and magnetic resonan...

Single-cell multi-omics dissection of RevitalAge Markers uncovers age-dependent immunotherapy resistance and druggable targets in melanoma.

Aging-related molecular reprogramming profoundly influences melanoma progression and therapeutic sen...

Digital Dermatology.

Digital transformation is fundamentally reshaping dermatology, creating new opportunities in diagnos...

Abdominal Dual-Energy CT with Deep Learning Reconstruction: Preserving Image Quality and Hepatic Lesion Conspicuity with Reduced Radiation and Contrast.

The objective was to evaluate the image quality and hepatic lesion conspicuity in a dual-low-dose (r...

Deep-Learning Solution Providing Molecular Marker Subtyping of Breast Cancer Whole Slide Images: Protocol for a UK Clinical Service Evaluation Study.

BACKGROUND: As the histopathology workforce continues to struggle and service demand continues to in...

Comparative Evaluation of Proximal Caries Detection Methods using Human, Artificial Intelligence, and Micro-CT Assessments.

OBJECTIVE: To validate the diagnostic accuracy of ICDAS visual examination, conventional bitewing ra...

Clinically actionable classification tool for childhood and adult atopic dermatitis via explainable AI: a retrospective cross-sectional study optimizing diagnostic accuracy.

BACKGROUND: Despite the critical role of early identification in managing atopic dermatitis (AD), cu...

Gold-Functionalized Multilayer Heterojunction Microarchitectures Enable High-Fidelity Serum Metabolite Profiling for Skin Cancer Subtype Classification.

Skin cancer is among the most prevalent malignancies worldwide, with non-melanoma types ranking amon...

Drug-induced multisystem syndromes: An overlooked challenge in pharmacovigilance.

BackgroundDrug-Induced Multisystem Syndromes (DIMS) represent a clinically significant yet under-rec...

Integrating machine learning-based molecular design with experimental validation for the discovery of EGFR inhibitors in lung cancer.

The emergence of drug resistance and off-target toxicities in epidermal growth factor receptor (EGFR...

Robust artificial intelligence frameworks for lung cancer subtyping and malignancy detection on thoracic CT.

Accurate characterization of thoracic malignancies on computed tomography (CT) remains challenging b...

Effectiveness of Artificial Intelligence in the Automatic Diagnosis of Lesions Detected in Panoramic Radiographs.

This study was aimed at evaluating the effectiveness of artificial intelligence (AI) in detecting ja...

Artificial intelligence (AI)-powered imaging for objective psoriasis severity assessment at home: Feasibility and reliability in a randomized clinical trial.

Deep learning reconstruction for chest MRI: image quality and diagnostic agreement with CT.

PURPOSE: To evaluate whether deep learning reconstruction (DLR) improves chest magnetic resonance im...

The diagnostic accuracy of AI-assisted diabetic retinopathy screening in primary care: a prospective validation study.

OBJECTIVES: This study investigated the diagnostic accuracy of AI-assisted diabetic retinopathy scre...

Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: Clinical insights, pitfalls, and observer agreement analyses.

PURPOSE: This study addresses critical gaps in automated lymphoma segmentation from PET/CT imaging, ...