Medical Ethics / Professional Responsibility

Integrating heterogeneity into topologically associating domain boundary prediction in large genomic context in human.

A fundamental understanding of genome organization relies on accurately annotating topologically associating domains (TADs) and their boundaries. This is crucial for understanding how cis-regulatory elements regulate gene expression. To go beyond calling TADs and boundaries from Hi-C data, several machine learning-based methods have been proposed to go the step further and predict TAD boundaries f...

A Novel Adversarial Approach for EEG Dataset Refinement: Enhancing Generalization Through Proximity-to-Boundary Scoring.

As deep learning (DL) performs remarkably in pattern recognition from complex data, it is used to interpret user intentions from electroencephalography (EEG) signals. However, the DL models trained on EEG datasets have low generalization ability owing to numerous noisy samples in datasets. Therefore, prior research has focused on distinguishing and eliminating noisy samples from datasets. One intu...

Multimodal and fair artificial intelligence in paediatric rheumatology: challenges and opportunities for a holistic and equitable future.

Multimodal artificial intelligence (AI) is an emerging domain comprising a set of tools with potential clinical relevance in paediatric rheumatology, ...

Regulatory Research Priorities for AI Use in the Medicine Lifecycle: A European Perspective with Global Relevance.

Regulatory bodies play a central role in providing guidance that enables safe and effective use of artificial intelligence tools in medicine developme...

Benchmarking Deep Segmentation Architectures for Histopathological Nuclei Segmentation: A Controlled Study of Transfer Learning, Robustness, and Efficiency Across CNN, Transformer, and Hybrid Models.

Accurate nuclei segmentation is essential for quantitative histopathological analysis and downstream clinical applications such as cancer grading, bio...

Critical Care-Specific vs General-Purpose Large Language Models in Emergency Intensive Care Unit Diagnosis: Single-Center Retrospective Paired Comparative Study.

BACKGROUND: The emergency intensive care unit (EICU) manages the most critically ill patients, where rapid and accurate diagnosis is essential yet cha...

Semantic segmentation and quantitative analysis of tunnel cracks and water leakage using a TransUNet framework.

As a vital component of structural health monitoring, the detection of cracks and water leakage in tunnel linings is essential for ensuring structural...

Rapid assessment of contaminant migration in complex heterogeneous aquifers via transferable attention-enhanced graph neural networks.

Highly heterogeneous aquifer structures and complex boundary disturbances pose persistent challenges for predicting the fate and transport of hazardou...

Contextrast++: Robust Multi-Scale Contextual Contrastive Learning for Semantic Segmentation.

Semantic segmentation has rapidly advanced with deep learning; however, challenges remain in effectively capturing local and global contexts as well a...

Must Every Dental Student Become Digitally Competent? Lessons From Prosthodontic Education in Southeast Asia.

INTRODUCTION: Digital technologies, including intraoral scanners, computer-aided design/computer-aided manufacturing (CAD/CAM), cone-beam computed tom...

Contextualized Malignantization: Morphometric Signatures of Breast Tissue Transformation and a Clinically Translatable Diagnostic Algorithm.

BACKGROUND: The transformation from benign to malignant breast tissue represents a complex biological continuum rather than a discrete pathological sw...

Physician oath, followership and leadership.

Physician oaths are often treated as ceremonial relics or ethical ornaments of graduation. I have come to think they are something more demanding: ear...

A polyline searching-driven evolutionary AI for disease detection of medical imaging data.

Objective Accurate Ultrasound (US) prostate cancer (PCa) segmentation images hold significant value for organ interventional guidance and clinical...

BAASNet: boundary-aware deep learning for accurate polyp segmentation in colonoscopy.

Colorectal polyps are primarily detected through colonoscopy, which plays a central role in early cancer prevention. Precise polyp segmentation suppor...

Use, Concerns, and Perspectives on AI in Health Care Among French Health Professionals and Students: Web-Based Cross-Sectional Survey.

BACKGROUND: AI is increasingly discussed and deployed in health care, yet safe and effective implementation depends on the preparedness, trust, and tr...

Patient-Level Cross-validated nnU-Net for Multiclass Segmentation of Lung Parenchyma and Solid Adenocarcinoma on Thoracic CT.

Automated segmentation of lung parenchyma and solid lung adenocarcinoma on thoracic computed tomography (CT) is needed for reproducible quantitative i...

Stress-Constrained Physics-Informed UNet for Voxel-Wise Multiparameter Hyperelastic Inversion in Volumetric Medical Imaging.

PURPOSE: To develop and evaluate a stress-constrained physics-informed UNet framework for voxel-wise, multiparameter hyperelastic characterization of ...

Three-class radiomic differentiation of hepatocellular carcinoma, intrahepatic cholangiocarcinoma, and combined hepatocellular-cholangiocarcinoma on multiphasic contrast-enhanced CT.

PURPOSE: Preoperative differentiation of hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and combined hepatocellular-cholangioc...

Regulatory Approaches to Cybersecurity Risk Management for AI-Enabled Medical Device Software in Korea, the United States, and the European Union: Comparative Document Analysis.

BACKGROUND: Software-based and AI-enabled medical devices are increasingly networked and updatable, expanding the attack surface and making cybersecur...

Manual federated simulation for multiple sclerosis integrating XGBoost algorithm with SHAP explanation.

Multiple sclerosis (MS) is a chronic autoimmune disorder of the central nervous system, underscoring the importance of early and accurate diagnosis. I...