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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 316-336 of 3,901 articles
Deep learning-based carotid media-adventitia and lumen-intima boundary segmentation from three-dimensional ultrasound images.

PURPOSE: Quantification of carotid plaques has been shown to be important for assessing as well as m...

Locally linear SVMs based on boundary anchor points encoding.

In this paper, we propose a locally linear classifier based on boundary anchor points encoding (LLBA...

MCRDR Knowledge-Based 3D Dialogue Simulation in Clinical Training and Assessment.

Dialogue-based simulation is a real-world practice technique for medical and clinical education that...

Smoothing dense spaces for improved relation extraction between drugs and adverse reactions.

BACKGROUND AND OBJECTIVE: This work aims at extracting Adverse Drug Reactions (ADRs), i.e. a harm di...

Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound.

Automatic prostate segmentation in transrectal ultrasound (TRUS) images is of essential importance f...

A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records.

BACKGROUND: The Named Entity Recognition (NER) task as a key step in the extraction of health inform...

Canadian Association of Radiologists White Paper on Ethical and Legal Issues Related to Artificial Intelligence in Radiology.

Artificial intelligence (AI) software that analyzes medical images is becoming increasingly prevalen...

CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation.

Accurate segmentation of the prostate and organs at risk (e.g., bladder and rectum) in CT images is ...

Modeling second-order boundary perception: A machine learning approach.

Visual pattern detection and discrimination are essential first steps for scene analysis. Numerous h...

Prior Information Guided Regularized Deep Learning for Cell Nucleus Detection.

Cell nuclei detection is a challenging research topic because of limitations in cellular image quali...

Disease vocabulary size as a surrogate marker for physicians' disease knowledge volume.

OBJECTIVE: Recognizing what physicians know and do not know about a particular disease is one of the...

'Artiphysiology' reveals V4-like shape tuning in a deep network trained for image classification.

Deep networks provide a potentially rich interconnection between neuroscientific and artificial appr...

Mixture Model Segmentation System for Parasagittal Meningioma brain Tumor Classification based on Hybrid Feature Vector.

Meningioma is the one of the most common type of brain tumor, it as arises from the meninges and enc...

Information-Based Boundary Equilibrium Generative Adversarial Networks with Interpretable Representation Learning.

This paper describes a new image generation algorithm based on generative adversarial network. With ...

Dense Associative Memory Is Robust to Adversarial Inputs.

Deep neural networks (DNNs) trained in a supervised way suffer from two known problems. First, the m...

Registration-Based Organ Positioning and Joint Segmentation Method for Liver and Tumor Segmentation.

The automated segmentation of liver and tumor from CT images is of great importance in medical diagn...

Modeling growth limits of Bacillus spp. spores by using deep-learning algorithm.

Growth/no growth boundary models for Bacillus spores that accounted for the effects of environmental...

Convolutional Neural Network for Segmentation and Measurement of Intima Media Thickness.

The measurement of Carotid Intima Media Thickness (IMT) on Common Carotid Artery (CCA) is a principl...

RACE-Net: A Recurrent Neural Network for Biomedical Image Segmentation.

The level set based deformable models (LDM) are commonly used for medical image segmentation. Howeve...

3D Tooth Segmentation and Labeling Using Deep Convolutional Neural Networks.

In this paper, we present a novel approach for 3D dental model segmentation via deep Convolutional N...

Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation.

Segmentation of liver in abdominal computed tomography (CT) is an important step for radiation thera...

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