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Medical Ethics / Professional Responsibility

Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.

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Showing 43-63 of 3,901 articles
CUAMT: A MRI semi-supervised medical image segmentation framework based on contextual information and mixed uncertainty.

BACKGROUND AND OBJECTIVE: Semi-supervised medical image segmentation is a class of machine learning ...

VMKLA-UNet: vision Mamba with KAN linear attention U-Net.

In the domain of medical image segmentation, while convolutional neural networks (CNNs) and Transfor...

Enhancing security in electromagnetic radiation therapy using fuzzy graph theory.

This research investigates the application of fuzzy graph theory to address critical security challe...

DCATNet: polyp segmentation with deformable convolution and contextual-aware attention network.

Polyp segmentation is crucial in computer-aided diagnosis but remains challenging due to the complex...

Enhancing cell instance segmentation in scanning electron microscopy images via a deep contour closing operator.

Accurately segmenting and individualizing cells in scanning electron microscopy (SEM) images is a hi...

Hot Injection Assisted Electronically Modulated Twin and Grain Boundary Rich Sub-2 nm PtCo Alloy Resistant to Phosphate Ion for PEMFCs.

Modulation of the electronic d-band center, structural defects (line defects), and particle size of ...

Design and Development of a Public AI Referee Assistance System Based on Harmony OS Platform.

The Hawkeye system was regarded as a successful and effective referee assistant in commercial applic...

Modelling fourth-order hyperelasticity in soft solids using physics informed neural networks without labelled data.

Mild traumatic brain injury can result from shear shock wave formation in the brain in the event of ...

Role of physics-informed constraints in real-time estimation of 3D vascular fluid dynamics using multi-case neural network.

Numerical simulations of fluid dynamics in tube-like structures are important to biomedical research...

BSA-Seg: A Bi-level sparse attention network combining narrow band loss for multi-target medical image segmentation.

Segmentation of multiple targets of varying sizes within medical images is of significant importance...

A hybrid object detection approach for visually impaired persons using pigeon-inspired optimization and deep learning models.

Visually challenged persons include a significant part of the population, and they exist all over th...

Boundary-enhanced local-global collaborative network for medical image segmentation.

Medical imaging plays a vital role as an auxiliary tool in clinical diagnosis and treatment, with se...

Low-cost sensor-based algal bloom labeling: a comparative study of SVM and logic methods.

This study explores a low-cost sensor system for real-time algae bloom detection and water managemen...

Effective Semi-Supervised Medical Image Segmentation With Probabilistic Representations and Prototype Learning.

Label scarcity, class imbalance and data uncertainty are three primary challenges that are commonly ...

Comparative analysis of deep learning architectures for breast region segmentation with a novel breast boundary proposal.

Segmentation of the breast region in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) ...

Segment Like A Doctor: Learning reliable clinical thinking and experience for pancreas and pancreatic cancer segmentation.

Pancreatic cancer is a lethal invasive tumor with one of the worst prognosis. Accurate and reliable ...

Vision Mamba and xLSTM-UNet for medical image segmentation.

Deep learning-based medical image segmentation methods are generally divided into convolutional neur...

Enhanced glioma tumor detection and segmentation using modified deep learning with edge fusion and frequency features.

Computer-aided automatic brain tumor detection is crucial for timely diagnosis and treatment, especi...

Enhancing biomedical named entity recognition with parallel boundary detection and category classification.

BACKGROUND: Named entity recognition is a fundamental task in natural language processing. Recognizi...

Raman spectroscopy for colorectal tumor margin assessment: A promising tool for real-time surgical delimitation.

Raman spectroscopy is a promising non-invasive technique not only for the rapid and accurate detecti...

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