Hospital-Based Medicine

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Latest AI and machine learning research in intensivists for healthcare professionals.

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Multi-modal contrastive mutual learning and pseudo-label re-learning for semi-supervised medical image segmentation.

Semi-supervised learning has a great potential in medical image segmentation tasks with a few labele...

Multi-Object Detection in Security Screening Scene Based on Convolutional Neural Network.

The technique for target detection based on a convolutional neural network has been widely implement...

Multi-Aspect enhanced Graph Neural Networks for recommendation.

Graph neural networks (GNNs) have achieved remarkable performance in personalized recommendation, fo...

Collaborative Damage Detection Framework for Rail Structures Based on a Multi-Agent System Embedded with Soft Multi-Functional Sensors.

With the rapid growth of railways in China, the focus has changed to the maintenance of large-scale ...

Do you need sharpened details? Asking MMDC-Net: Multi-layer multi-scale dilated convolution network for retinal vessel segmentation.

Convolutional neural networks (CNN), especially numerous U-shaped models, have achieved great progre...

Multi-environment robotic transitions through adaptive morphogenesis.

The current proliferation of mobile robots spans ecological monitoring, warehouse management and ext...

Edge-Aware Graph Neural Network for Multi-Hop Path Reasoning over Knowledge Base.

Multi-hop path reasoning over knowledge base aims at finding answer entities for an input question b...

An efficient and low complex model for optimal RBM features with weighted score-based ensemble multi-disease prediction.

Multi-disease prediction is regarded as the capacity to simultaneously identify various diseases tha...

Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images.

Accurate and rapid diagnosis of coronavirus disease 2019 (COVID-19) from chest CT scans is of great ...

Designing all-pay auctions using deep learning and multi-agent simulation.

We propose a multi-agent learning approach for designing crowdsourcing contests and All-Pay auctions...

Multi-omics disease module detection with an explainable Greedy Decision Forest.

Machine learning methods can detect complex relationships between variables, but usually do not expl...

Modality attention fusion model with hybrid multi-head self-attention for video understanding.

Video question answering (Video-QA) is a subject undergoing intense study in Artificial Intelligence...

The Emerging Trends of Multi-Label Learning.

Exabytes of data are generated daily by humans, leading to the growing needs for new efforts in deal...

Path planning and collision avoidance methods for distributed multi-robot systems in complex dynamic environments.

Multi-robot systems are experiencing increasing popularity in joint rescue, intelligent transportati...

A Parallel Classification Model for Marine Mammal Sounds Based on Multi-Dimensional Feature Extraction and Data Augmentation.

Due to the poor visibility of the deep-sea environment, acoustic signals are often collected and ana...

Applications of complex picture fuzzy soft power aggregation operators in multi-attribute decision making.

The major theme of this analysis is to suggest a new theory in the form of complex picture fuzzy sof...

Multi-scopic neuro-cognitive adaptation for legged locomotion robots.

Dynamic locomotion is realized through a simultaneous integration of adaptability and optimality. Th...

A novel MCF-Net: Multi-level context fusion network for 2D medical image segmentation.

Medical image segmentation is a crucial step in the clinical applications for diagnosis and analysis...

Multi-Modal Deep Learning for Assessing Surgeon Technical Skill.

This paper introduces a new dataset of a surgical knot-tying task, and a multi-modal deep learning m...

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