Medical Ethics / Professional Responsibility

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 sea surface critical. In this field, Polarimetric Synthetic Aperture Radar (PolSAR) is an effective tool to identify oil spills. However, two main limitations exist in current researches: on the one hand, they fail to take full advantage of the polari...

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 ...

Privacy emotion recognition in artificial intelligence: Research frontiers, key challenges, and prospects.

With the arrival of the new wave of artificial intelligence, emotional intelligence has broad application prospects. By quantifying the psychological ...

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...

AI disclosure uncertainty in nursing education: A pedagogical scaffold for professional learning.

Generative artificial intelligence (AI) is rapidly reshaping how nursing students produce and communicate academic work, intensifying questions about ...

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...

A hierarchical and privacy-preserving intrusion detection framework for SAGIN-enabled IIot using graph neural networks and deep Q-learning.

Space-Air-Ground Integrated Networks (SAGIN) supporting Industrial Internet of Things (IIoT) applications impose stringent requirements on intrusion 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...