Medical Ethics / Professional Responsibility

Resolving the multiscale design trade-off in bone tissue engineering: From generative design to digital twins.

The clinical translation of bone tissue engineering is constrained by a severe multiscale design trade-off: the requirement for load-bearing mechanical strength competes directly with the need for vascular-permissive porosity. Conventional approaches address scaffold geometry, material formulation, and fabrication in a sequential, decoupled manner and therefore fail to navigate this multi-objectiv...

SAM2HIPT: A hybrid deep learning framework integrating SAM2 and HIPT with joint loss optimization for immunohistochemical cell nucleus segmentation.

Nucleus segmentation in immunohistochemistry (IHC) images plays a critical role in cancer diagnosis and treatment assessment. However, existing methods remain limited in segmentation accuracy and boundary delineation due to staining heterogeneity, densely packed cell distributions, and complex background interference. To address these challenges, this paper proposes a two-stage nucleus segmentatio...

Oil spill detection on sea surface with dual-polarimetric SAR imagery integrating polarization features and oil-seawater boundary information.

Oil Spill can cause a series of ecological disasters and irreversible damages to marine environment, making the timely detection of oil films on the s...

Electrophysiologically informed spiking neural networks for fish-inspired navigation with boundary vector cells and hydrostatic pressure cues.

Spatial memory is a fundamental cognitive capacity governing the mental encoding of spatial information, which can be used to navigate through intrica...

The finite element neural network method to simulate two dimensional partial differential equations and perform parameter identification.

Neural networks (NNs) have received growing interest in engineering due to their ability to assimilate high-dimensional data and provide accurate appr...

AI-Generated Clinical Images of Head-and-Neck Lesions in Plastic Surgery Education: An Expert Evaluation.

BACKGROUND: Clinical images are essential in plastic and reconstructive surgery education, particularly for understanding pathology, planning reconstr...

A dataset of high-resolution snapshots of the viscous sublayer from direct numerical simulation of a turbulent boundary layer up to Re θ=2400.

This dataset comprises time-resolved 3D fluid field data (pressure and the three velocity components) from the viscous sublayer of a canonical zero-pr...

Use and Perceptions of Large Language Models Among Dental Students: Implications for Dental Education.

PURPOSE: This study aimed to quantify the prevalence and use cases of large language models (LLMs) among dental students, estimate perceived usefulnes...

Privacy-preserving multimodal federated learning pipeline for cyber-resilient healthcare systems.

The integration of Internet of Things (IoT) devices and electronic medical records (EMRs) has transformed healthcare delivery but has also created new...

Segmenting multi-modal abdominal multi-organ using the CADSTransN-Net model.

Deep learning advances medical imaging segmentation, but the insufficient diversity of datasets limits its performance. The AMOS22 dataset addresses t...

Artificial intelligence in scholarly peer review: a scoping review of applications, risks, and governance challenges.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into scholarly publishing workflows, extending beyond manuscript preparation into ...

Deep Learning-based Segmentation for Assessment of Kidney Tumour Ablation Therapy in CT Images.

Kidney tumor ablation is a minimally invasive treatment for Renal Cell Carcinoma (RCC). Manual segmentation of the kidney ablation zone (KAZ) is time-...

A multi-modal data fusion and real-time monitoring on stroke risk prediction using federated learning.

Predicting the risk of stroke is one of the critical problems in healthcare, which necessitates efficient solutions for providing accurate and prompt ...

Multi-parameter deep learning for robust fiber eavesdropping detection and temporal localization.

As the backbone of global communication infrastructure, optical fibers carry vast amounts of sensitive data, making them prime targets for eavesdroppi...

Legendre neural network-based computational study through hybrid particle swarm optimization for fractional unsteady flow of Sutterby fluid.

This study investigates the two-dimensional unsteady flow of a Sutterby fluid over a stretching surface under no slip boundary condition with addition...

BGSC-Net: Boundary-guided semantic compensation network for remote sensing image segmentation.

Deep learning has recently made remarkable progress in remote sensing image segmentation, with hybrid architectures that integrate convolutional neura...

A field boundary dataset for the canadian prairies derived from sentinel-2 imagery using the segment anything model.

This article presents a Prairie-wide spatial vector dataset of agricultural field boundaries across Alberta, Saskatchewan, and Manitoba, Canada. The d...

FedGA: Genetic Algorithm-Guided Federated Learning for Medical Image Segmentation with Non-IID Features.

Federated learning (FL) enhances data privacy and compliance with data regulations by enabling multiple decentralized parties to collaboratively train...

Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults Using Source-Free Domain Adaptation: Algorithm Development and Validation.

BACKGROUND: Cognitive decline in the aging population presents an unprecedented challenge worldwide. Recent research has shown the potential of cognit...

Text-guided automatic segmentation of clinical target volume in rectal cancer radiotherapy.

OBJECTIVE: Current automatic segmentation models in radiotherapy, which are predominantly unimodal and image-based, have limited generalizability due ...