Medical Ethics / Professional Responsibility

Boundary sensitive-net-based lumbar vertebra segmentation and spondylolisthesis measurement.

Lumbar spine disorders represent a significant public health concern, with accurate diagnosis relying on vertebral segmentation and quantification. Traditional methods, such as Cobb angle measurement are constrained by two-dimensional projections, while cumulative segmentation and quantification errors limit automated CT analysis. To overcome these issues, this paper proposes a deep learning-based...

Spinal disease image segmentation technology integrating U-ResNet and shape-aware attention.

The incidence of spinal diseases is rising and affecting younger people, making early and accurate diagnosis based on medical imaging crucial for treatment. However, traditional manual segmentation and measurement suffer from issues such as judgment discrepancies, time-consuming processes, and subjective errors. Existing deep learning segmentation methods still face challenges such as insufficient...

An Enhanced Low-Computational-Complexity Predefined-Time Convergent Zeroing Neural Network for Constrained Time-Varying Quadratic Programming With Kinematic Control of Robotic Manipulator.

Time-varying quadratic programming (TVQP) problems can be regarded as a challenging issue in a wide range of engineering applications, frequently inco...

LLM-based keyword augmentation for title-driven evidence selection: A practical approach.

Keyword-based search is widely used in digital forensic investigations, yet its effectiveness depends strongly on investigator experience, leading to ...

External-knowledge enhanced dual encoder and contrastive learning for aspect sentiment triplet extraction.

Aspect Sentiment Triplet Extraction (ASTE) is an emerging subtask of Aspect-Based Sentiment Analysis (ABSA), aiming to extract aspect terms, opinion t...

Deep learning-based HTTP TRACE flood detection in wireless sensor network using deep spectral multi-layer convolutional neural network.

Wireless Sensor Networks (WSN) are widely used across various fields. WSN is composed of many low-cost, high-performance, plug-and-play sensor nodes. ...

Medical Student Experiences With ChatGPT: National Cross-Sectional Study.

BACKGROUND: Artificial intelligence (AI) is increasingly influencing medical student education, with AI-driven chatbots, such as ChatGPT, emerging as ...

Geometry-aware PointNet for rapid prediction of cerebral aneurysm hemodynamics.

BACKGROUND AND OBJECTIVE: Cerebral aneurysms affect 2-5% of the global population and pose a significant health risk upon rupture. While computational...

The utility of large language models in oncological multidisciplinary team meetings: A systematic review.

Large language models (LLMs) have emerged in recent years as innovative artificial intelligence systems with early potential in clinical decision-maki...

Forecasting-based biomedical time-series data synthesis for open data and robust AI.

The limited data availability due to strict privacy regulations and significant resource demands severely constrains biomedical time-series AI develop...

NeuroCardioSense (NCS): A Time-Aware Fuzzy Decision Framework for Multi-Lead ECG Classification and Arrhythmia Detection.

Accurate classification of electrocardiogram (ECG) signals is essential for automated arrhythmia detection and clinical decision support. Existing dee...

From principle to practice: Developing a digital-age clinical artificial intelligence ethics competence framework through early-career doctors' experiences.

INTRODUCTION: As artificial intelligence (AI) becomes increasingly embedded in clinical workflows, clinicians encounter ethical challenges that tradit...

Performance of deep learning-based segmentation of soft tissue sarcoma by MRI sequence, tumor type and location.

OBJECTIVE: Soft tissue sarcomas (STS) are a rare and heterogeneous group of tumors that pose a significant challenge for surgical planning. This study...

Constructing digital professionalism in the generative AI era: A qualitative study with nursing students and faculty.

BACKGROUND: Generative artificial intelligence (AI) is entering coursework, simulation, and assessment in nursing programs. Conventional digital profe...

MsM-DPM: Multiscale Mamba Diffusion Probabilistic Model for Medical Image Segmentation.

Diffusion probabilistic models (DPMs) have recently demonstrated promising performance in medical image segmentation. However, traditional DPM has dif...

Inverse design method of optical devices for generating target near-fields via physics-informed neural networks.

We propose a method for inverse design of optical devices to generate target near-fields using physics-informed neural networks (PINNs). A finite-diff...

IoT framework for sports activity safety monitoring based on wearable sensors and CRNN spatiotemporal analysis.

The integration of wearable sensors and IoT technology provides new technical means for sports activity monitoring. However, existing solutions still ...

Embedding Artificial Intelligence Competencies in Military Medical Education: A Longitudinal Framework.

Artificial intelligence (AI) is rapidly transforming healthcare delivery, logistics, and operational decision-making across the Military Health System...

Findings from a transformer-based prediction model: social norms and confidentiality are associated with STIs risk in British men and women.

Responsible use of large language models in manuscript authorship, peer review, and editorial processes: a Delphi consensus among editors-in-chief of anaesthesia and pain medicine journals (RULE-AP).

This article presents a Delphi consensus developed by a panel of editors-in-chief of anaesthesiology and pain medicine journals to guide the responsib...