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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 274-294 of 3,901 articles
Retinal Boundary Segmentation in Stargardt Disease Optical Coherence Tomography Images Using Automated Deep Learning.

PURPOSE: To use a deep learning model to develop a fully automated method (fully semantic network an...

Boundary Mittag-Leffler stabilization of fractional reaction-diffusion cellular neural networks.

Mittag-Leffler stabilization is studied for fractional reaction-diffusion cellular neural networks (...

Ethical and Legal Challenges of Artificial Intelligence in Nuclear Medicine.

Artificial intelligence (AI) in nuclear medicine has gained significant traction and promises to be ...

Considerations for the Ethical Implementation of Psychological Assessment Through Social Media via Machine Learning.

The ubiquity of social media usage has led to exciting new technologies such as machine learning. Ma...

Localization of Biobotic Insects Using Low-Cost Inertial Measurement Units.

Disaster robotics is a growing field that is concerned with the design and development of robots for...

Pine Cone Detection Using Boundary Equilibrium Generative Adversarial Networks and Improved YOLOv3 Model.

The real-time detection of pine cones in Korean pine forests is not only the data basis for the mech...

CAS: corpus of clinical cases in French.

BACKGROUND: Textual corpora are extremely important for various NLP applications as they provide inf...

Intermittent boundary stabilization of stochastic reaction-diffusion Cohen-Grossberg neural networks.

Cohen-Grossberg neural networks (CGNNs) play an important role in many applications and the stabiliz...

Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images.

Incorporating human domain knowledge for breast tumor diagnosis is challenging because shape, bounda...

Discretely-constrained deep network for weakly supervised segmentation.

An efficient strategy for weakly-supervised segmentation is to impose constraints or regularization ...

Deep-learning-based accurate hepatic steatosis quantification for histological assessment of liver biopsies.

Hepatic steatosis droplet quantification with histology biopsies has high clinical significance for ...

Evaluation of mental workload during automobile driving using one-class support vector machine with eye movement data.

The aim of this study is to investigate the usefulness of the anomaly detection method by one-class ...

Supervised machine learning for coronary artery lumen segmentation in intravascular ultrasound images.

Intravascular ultrasound (IVUS) has been widely used to capture cross sectional lumen frames of inne...

Ultrasound Deep Learning for Wall Segmentation and Near-Wall Blood Flow Measurement.

Studies of medical flow imaging have technical limitations for accurate analysis of blood flow dynam...

On the boundary conditions of avoidance memory reconsolidation: An attractor network perspective.

The reconsolidation and extinction of aversive memories and their boundary conditions have been exte...

Applying Deep Neural Networks over Homomorphic Encrypted Medical Data.

In recent years, powered by state-of-the-art achievements in a broad range of areas, machine learnin...

CPFNet: Context Pyramid Fusion Network for Medical Image Segmentation.

Accurate and automatic segmentation of medical images is a crucial step for clinical diagnosis and a...

Optic Disc and Cup Image Segmentation Utilizing Contour-Based Transformation and Sequence Labeling Networks.

Optic disc (OD) and optic cup (OC) segmentation are important steps for automatic screening and diag...

Modeling the Research Landscapes of Artificial Intelligence Applications in Diabetes (GAP).

The rising prevalence and global burden of diabetes fortify the need for more comprehensive and effe...

Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN).

The medical and machine learning communities are relying on the promise of artificial intelligence (...

Imaging research in fibrotic lung disease; applying deep learning to unsolved problems.

Over the past decade, there has been a groundswell of research interest in computer-based methods fo...

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