Critical Care

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

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Subcategories: Sepsis
Showing 3025-3045 of 7,452 articles
Privacy-enhanced multi-party deep learning.

In multi-party deep learning, multiple participants jointly train a deep learning model through a ce...

Deep representation learning for individualized treatment effect estimation using electronic health records.

Utilizing clinical observational data to estimate individualized treatment effects (ITE) is a challe...

Multi-task recurrent convolutional network with correlation loss for surgical video analysis.

Surgical tool presence detection and surgical phase recognition are two fundamental yet challenging ...

DCCMED-Net: Densely connected and concatenated multi Encoder-Decoder CNNs for retinal vessel extraction from fundus images.

Recent studies have shown that convolutional neural networks (CNNs) can be more accurate, efficient ...

ICU staffing feature phenotypes and their relationship with patients' outcomes: an unsupervised machine learning analysis.

PURPOSE: To study whether ICU staffing features are associated with improved hospital mortality, ICU...

Clinical applications of artificial intelligence in sepsis: A narrative review.

Many studies have been published on a variety of clinical applications of artificial intelligence (A...

Missing MRI Pulse Sequence Synthesis Using Multi-Modal Generative Adversarial Network.

Magnetic resonance imaging (MRI) is being increasingly utilized to assess, diagnose, and plan treatm...

Machine Learning Approach for Prediction of Hematic Parameters in Hemodialysis Patients.

This paper shows the application of machine learning techniques to predict hematic parameters using...

Adaptive latent similarity learning for multi-view clustering.

Most existing clustering methods employ the original multi-view data as input to learn the similarit...

Non-faradaic electrochemical impedimetric profiling of procalcitonin and C-reactive protein as a dual marker biosensor for early sepsis detection.

In this work, we demonstrate a robust, dual marker, biosensing strategy for specific and sensitive e...

Endocan serum concentration in uninfected newborn infants.

INTRODUCTION: Endocan is a specific endothelial mediator involved in the inflammatory response. Its ...

Self Multi-Head Attention-based Convolutional Neural Networks for fake news detection.

With the rapid development of the internet, social media has become an essential tool for getting in...

Multi-criterion mammographic risk analysis supported with multi-label fuzzy-rough feature selection.

CONTEXT AND BACKGROUND: Breast cancer is one of the most common diseases threatening the human lives...

Leveraging implicit expert knowledge for non-circular machine learning in sepsis prediction.

Sepsis is the leading cause of death in non-coronary intensive care units. Moreover, a delay of anti...

Levels of Soluble Urokinase Plasminogen Activator Receptor in Pediatric Lower Respiratory Tract Infections.

Lower respiratory tract infections (LTRIs) are the most common cause of pediatric emergency departm...

Technical considerations of multi-parametric tissue outcome prediction methods in acute ischemic stroke patients.

Decisions regarding acute stroke treatment rely heavily on imaging, but interpretation can be diffic...

Retrospective Observational Study of the Clinical Performance Characteristics of a Machine Learning Approach to Early Sepsis Identification.

UNLABELLED: To estimate performance characteristics and impact on care processes of a machine learni...

Deep Multi-View Feature Learning for EEG-Based Epileptic Seizure Detection.

Epilepsy is a neurological illness caused by abnormal discharge of brain neurons, where epileptic se...

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