Dermatology

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 assessment is critical but remains limited by the subjective and limited nature of slit-lamp and anterior segment optical coherence tomography (AS-OCT) assessments. This study presents the 'Intelligent Quantitative Keratitis Image Analysis Platform', a web-based deep learning system for automated IK asses...

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 improving clinical outcomes in early-stage breast cancer (EBC). A multimodal deep learning model (Mu-model) based on deep canonical correlation analysis (DCCA) integrating multiparametric magnetic resonance imaging (MRI)-including dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imagin...

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 resonance imaging (MRI) radiomics to predict 1-year effic...

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 sensitivity, yet underlying mechanisms remain poorly ...

Digital Dermatology.

Digital transformation is fundamentally reshaping dermatology, creating new opportunities in diagnostics, therapy, and healthcare organization. Large ...

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 (radiation and contrast volume) upper abdominal dual...

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 increase, it has become prudent to consider viable a...

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 radiography, and artificial intelligence (AI)-assist...

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), current studies are limited by the absence of adult-...

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 among the top five and melanoma characterized by high ...

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

BackgroundDrug-Induced Multisystem Syndromes (DIMS) represent a clinically significant yet under-recognized group of delayed immune-mediated adverse d...

A deep learning framework for lesion-level treatment response prediction in hodgkin lymphoma using PET/CT tensor radiomics.

BACKGROUND: Accurate prediction of treatment response in Hodgkin lymphoma (HL) is crucial for personalized therapy. The Tensor Radiomics (TR) paradigm...

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) targeted therapies underscores the urgent need f...

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 because histological subtype differentiation and no...

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 jaw cysts and tumors, analyzing lesion content, and ...

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 screening in primary care, using ophthalmologist-led s...

AI automated grid placement in the OMERACT knee inflammation MRI scoring system (KIMRISS) for bone marrow lesion assessment: A multi-reader exercise.

OBJECTIVE: To validate the reliability and feasibility of AI-automated grid placement for bone marrow lesion (BML) scoring in the Knee Inflammation MR...

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, often overlooked in prior work. While deep learnin...

Application Value of Radiomics-Based Machine Learning for Preoperative Risk Stratification of Bladder Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Some researchers have explored the application of radiomics-based machine learning to detect preoperative muscle invasion, high-grade tumo...

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lu...