Medical Ethics / Professional Responsibility

Invisible poison attacks and holistic defence strategy for pyramid vision transformers in medical imaging.

Machine learning models, especially vision transformers in the domain of medical images, are highly prone to data poisoning attacks, in which a small proportion of adversarial samples is injected into the model's training dataset to manipulate its behavior. Existing data poisoning techniques have their limitations in terms of the presence of noticeable artifacts in the injected samples or their vu...

Dynamic low-altitude airspace partitioning and management strategy optimization based on graph neural networks and spatial cognitive constraints.

The rapid expansion of urban air mobility operations demands adaptive airspace management approaches that transcend traditional static sectorization. This paper proposes an integrated framework for dynamic low-altitude airspace partitioning and management strategy optimization by fusing graph neural networks with spatial cognitive science. Urban low-altitude airspace is modeled as an attributed we...

Understanding Public Awareness, Attitudes, Beliefs, and Perceptions About ChatGPT in Saudi Arabia: A Road Map for Digital Health.

BACKGROUND Chat Generative Pre-Trained Transformer (ChatGPT) is an advanced artificial intelligence (AI) tool that has become increasingly integrated ...

Topology-decoupled end-to-end framework for brain tumor MRI detection: boundary-preserving feature flow and inter-channel correlation distillation.

Early and accurate detection of brain tumors is clinically valuable for improving prognosis and guiding treatment. Existing deep-learning methods for ...

Non-invasive coronary fractional flow reserve prediction using a neural network with hemodynamic and geometric embeddings: A proof-of-concept study.

BACKGROUND AND OBJECTIVES: Invasive fractional flow reserve (FFR) is the clinical gold standard for assessing coronary artery stenosis, but its applic...

Optimising chest computed tomography (CT) scan ranges in paediatric patients to reduce radiation exposure.

AIM: The aim of this study was to accurately position the scan range of unenhanced chest computed tomography (CT) scans for paediatric patients by cla...

Cloud-based healthcare architecture for securing and monitoring healthcare data.

PURPOSE: A new method known as Lionized Remora optimization based Recurrent Neural Network (LRObRNN) is recommended to enhance the safety of medical i...

Fine-Tuning Large Language Models for Motivational Interviewing in Health Behavior Change: Development and Evaluation Study.

BACKGROUND: Motivational interviewing (MI) is an effective counseling approach for promoting health behavior change, but its scalability is constraine...

Trust-driven healthy engagement with conversational AI for mental health support in young adults: a mixed methods study.

Young adults aged 18-35 years increasingly engage with conversational artificial intelligence (C-AI) in everyday contexts in which they may perceive e...

PINN for stiff moving-boundary PDE to predict the locking point in superheated steam drying.

Physics-informed neural networks (PINNs) often struggle to solve stiff partial differential equations (PDEs) with moving boundaries, such as convectio...

High-resolution UAV imagery-based instance segmentation for automatic counting of rubber trees across phenological seasons.

Accurate counting of rubber trees is important for yield estimation, refined field management, and the sustainable development of the rubber industry....

Boundary-Aware Spectral and Morphological Guidance Method for Feature-Driven Colorectal Cancer Segmentation.

Precise segmentation of medical images plays a crucial role in modern clinical practice, providing important foundations for the quantitative analysis...

Automated precise recognition of ovine embryo microscopic images using a boundary-enhanced deep learning network.

Efficient selection of in vitro-fertilized embryos is crucial for assisted reproduction in sheep, and automated microscopic analysis can enable object...

Validation of MRI-based nnU-Net model for automated segmentation of neck lymph nodes in head and neck squamous cell carcinoma: a multicenter study.

PURPOSE: To develop and externally validate an MRI-based deep learning framework for automated 3D segmentation of neck lymph nodes (LNs) in head and n...

Physics-informed convolutional neural networks for fluid flow through porous media.

Accurate simulation of fluid flow in porous media is a challenging task due to the complexity of pore-space geometries and the computational cost of s...

Direct Variational Calculation of Two-Electron Reduced Density Matrices via Semidefinite Machine Learning.

We introduce a data-driven framework for approximating the convex set of N-representable two-electron reduced density matrices (2-RDMs). Traditional a...

Ethical Considerations in Personal Health Large Language Models.

Personal health large language models (PH-LLMs) have rapidly evolved from research prototypes into consumer-facing, data-linked systems that support s...

Losing the hand on the wheel: AI trust, decision delegation, and displacement of responsibility in financial decision-making.

PURPOSE: As artificial intelligence (AI) becomes increasingly integrated into financial decision-making, concerns about responsibility attribution in ...

Balancing accuracy and efficiency in lumbar spine image segmentation using multi-scale attention and residual learning.

Accurate automated segmentation of Lumbar Spine Structures (LSS) in Magnetic Resonance Imaging (MRI) is important for effective diagnosis and treatmen...

Robust quantification of ICG fluorescence perfusion in neonatal bowel surgery via deep point tracking.

PURPOSE: Indocyanine green (ICG) fluorescence imaging is increasingly used for intraoperative bowel perfusion assessment in neonatal surgery. However,...