Medical Ethics / Professional Responsibility

Assessing the Evolution and Influence of Medical Open Databases on Biomedical Research and Health Care Innovation: A 25-Year Perspective With a Focus on Privacy and Privacy-Enhancing Technologies.

The integration of medical open databases with artificial intelligence (AI) technologies marks a transformative era in biomedical research and health care innovation. Over the past 25 years, initiatives like PhysioNet have revolutionized data access, fostering unprecedented levels of collaboration and accelerating medical discoveries. This rise of medical open databases presents challenges, partic...

Real-Time and Precise 3-D Lesion Reconstruction With Boundary Point Clouds for Robotic Ultrasound Scanning.

In robot-assisted breast ultrasound scanning, conventional 2-D imaging often fails to fully capture the spatial morphology of lesions, limiting clinicians' ability to obtain intuitive structural information. In addition, variations in patient body type and examination posture lead to significant scanning range fluctuations. Conventional voxel-based 3-D reconstruction methods rely heavily on pre-de...

Absence of dehydration due to superionic transition at Earth's core-mantle boundary.

The properties and stability of hydrous phases are crucial to unraveling the mysteries of the deep water cycle. Under deep lower mantle conditions, wa...

HCAR1 antagonist screening based on boundary-selected negative sampling strategy and multi-level graph neural network.

BACKGROUND AND OBJECTIVE: Hydroxycarboxylic acid receptor 1 (HCAR1), also known as the lactate receptor, is closely associated with tumorigenesis and ...

Fuzzy rough set loss for deep learning-based precise medical image segmentation.

Accurate segmentation of medical images is crucial for diagnosis and treatment planning, yet it remains challenging due to ambiguous lesion boundaries...

A hybrid federated learning framework with generative AI for privacy-preserving and sustainable security in IOT-enabled smart environments.

The dramatic increase in IoT devices in a smart ecosystem like smart cities, transportation systems, and healthcare and industrial automation has grea...

Machine learning and food inspection: use of Bayesian Network modeling to support official controls in the food industries.

This study aims to develop a machine learning model capable of predicting the type of non-compliance (NC) most likely to be detected by competent auth...

Deep Laplacian Coordinates: End-to-end deeply guided anisotropic diffusion for COVID-19 pulmonary lesion segmentation.

Despite notable advances in deep learning, accurately segmenting lung lesions in computed tomography remains a significant challenge due to the scarci...

Humane Intelligence in Geropsychiatric Care: Relational Artificial Intelligence, Clinical Wisdom, and the Moral Grid Operational Index.

Artificial intelligence (AI) already influences how older adults are identified for services, supported between provider visits, and referred for care...

When and how to disclose AI use in academic publishing: AMEE Guide No.192.

Generative Artificial Intelligence (GenAI) tools are increasingly integrated into research and academic writing, offering opportunities to streamline ...

Label Noise in Pathological Segmentation Is Overlooked, Leading to Potential Overestimation of Artificial Intelligence.

Artificial intelligence (AI) has transformed medical imaging, notably in radiology and endoscopy. Semantic segmentation, a pixel-level technique cruci...

CHAP: Channel-spatial hierarchical adversarial perturbation for semi-supervised medical image segmentation.

Semi-supervised medical image segmentation (SSMIS) methods predominantly rely on consistency regularization to reinforce invariant feature learning un...

A physics informed neural network architecture for moving boundary problems in science and engineering.

The study of moving boundary problems requires determining the moving interface which is a-priori unknown, significantly affecting the problem's physi...

Small data, big challenges: Machine- and deep-learning strategies for data-limited drug discovery.

A critical bottleneck limiting the potential of Machine Learning (ML) and Deep Learning (DL) models within the drug discovery and development (DDD) pi...

Beyond hard constraint: unified knowledge-embedding physics informed neural networks for multi-domain system.

PINNs, enabling the assimilation of physical laws and sparse observational data into deep models, have been a powerful method for rapid prediction of ...

A physics-embedded dual-learning imaging framework for electrical impedance tomography.

Electrical Impedance Tomography (EIT) is a promising noninvasive imaging technique that reconstructs the spatial conductivity distribution from bounda...

Automated grain analysis via data augmentation and grain boundary detection.

This study presents an AI-enhanced framework to address key challenges in the quantitative metallographic analysis of pure iron systems. Manual grain ...

Optimizing boundary dynamics for nested named entity recognition via semantic refinement and trimming.

Nested Named Entity Recognition (Nested NER) addresses the complex task of identifying and classifying entity spans embedded within other entities in ...

18F-FDG PET-based ensemble deep learning model for the prediction of lymphovascular invasion in colorectal cancer patients.

OBJECTIVE: The aim of this study was to investigate the diagnostic performance of the 2.5-dimensional (2.5D) ensemble deep learning (DL) model based o...

Internal-external boundary attention fusion for glass surface segmentation.

Detecting transparent objects and mirrors in an image is a highly challenging task because their glass surfaces contain the visual appearance of other...