Latest AI and machine learning research in critical care for healthcare professionals.
To address the incompleteness of knowledge graphs, multi-hop reasoning aims to find the unknown info...
STUDY OBJECTIVE: The aim of this study was to investigate whether goal-directed treatment using arti...
BACKGROUND: Sepsis remains a life-threatening condition in intensive care units (ICU) with high morb...
While multi-modal deep learning approaches trained using magnetic resonance imaging (MRI) and fluoro...
With the ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its i...
Real-world multi-agent decision-making systems often have to satisfy some constraints, such as harmf...
BACKGROUND: Online health communities (OHCs) enable people with long-term conditions (LTCs) to excha...
Accurately labeling large datasets is important for biomedical machine learning yet challenging whil...
This paper introduces an innovative multi-view stereo matching network-the Multi-Step Depth Enhancem...
ELM (Extreme learning machine) has drawn great attention due its high training speed and outstanding...
PURPOSE OF REVIEW: Critically ill children admitted to the intensive care unit frequently need respi...
Gene microarray technology provides an efficient way to diagnose cancer. However, microarray gene ex...
This study aims to explore the effect of implant apex design, osteotomy preparation, intraosseous de...
Multi-modality medical image fusion (MMIF) technology utilizes the complementarity of different moda...
Navigating multi-agent reinforcement learning (MARL) environments with sparse rewards is notoriously...
Recent advances in the design of convolutional neural networks have shown that performance can be en...
The variability in image modalities presents significant challenges in medical image classification,...
The detection and classification of arrhythmia play a vital role in the diagnosis and management of ...
UNLABELLED: The escalating therapeutic use of methadone has coincided with an increase in accidental...
This paper presents a digital edge neuromorphic spiking neural network (SNN) processor chip for a va...
This paper presents a supervised contrastive learning (SCL) framework for respiratory sound classifi...