Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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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...

Early prediction of hemodialysis complications employing ensemble techniques.

BACKGROUND AND OBJECTIVES: Hemodialysis complications remain a critical threat among dialysis patien...

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...

Biodegradable Smart Face Masks for Machine Learning-Assisted Chronic Respiratory Disease Diagnosis.

Utilizing smart face masks to monitor and analyze respiratory signals is a convenient and effective ...

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...

Integrative Histology-Genomic Analysis Predicts Hepatocellular Carcinoma Prognosis Using Deep Learning.

Cancer prognosis analysis is of essential interest in clinical practice. In order to explore the pro...

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...

Application of Visual Recognition Based on BP Neural Network in Architectural Design Optimization.

In order to establish the mapping relationship between architectural design parameters and building ...

Predicting respiratory motion using a novel patient specific dual deep recurrent neural networks.

Real-time tracking of a target volume is a promising solution for reducing the planning margins and ...

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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