Critical Care

Multi-scale approach for the prediction of atomic scale properties.

Electronic nearsightedness is one of the fundamental principles that governs the behavior of condens...

Identification of biological correlates associated with respiratory failure in COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a global public health concern. Recently, a genom...

Five novel clinical phenotypes for critically ill patients with mechanical ventilation in intensive care units: a retrospective and multi database study.

BACKGROUND: Although protective mechanical ventilation (MV) has been used in a variety of applicatio...

Hybrid-COVID: a novel hybrid 2D/3D CNN based on cross-domain adaptation approach for COVID-19 screening from chest X-ray images.

The novel Coronavirus disease (COVID-19), which first appeared at the end of December 2019, continue...

Moderate to severe leukocytosis with vasopressor use is associated with increased mortality in trauma patients.

BACKGROUND: Leukocytosis is a rise in white blood cell (WBC) count and clinical outcomes of moderate...

Functional Lung MRI: Deep Learning Turns Proton into Helium Ventilation Maps-The Battle Is On!

Pulmonary Ventilation Maps Generated with Free-breathing Proton MRI and a Deep Convolutional Neural Network.

Background Hyperpolarized noble gas MRI helps measure lung ventilation, but clinical translation rem...

Predicting 30-days mortality for MIMIC-III patients with sepsis-3: a machine learning approach using XGboost.

BACKGROUND: Sepsis is a significant cause of mortality in-hospital, especially in ICU patients. Earl...

MD-NDNet: a multi-dimensional convolutional neural network for false-positive reduction in pulmonary nodule detection.

Pulmonary nodule false-positive reduction is of great significance for automated nodule detection in...

Clinically applicable approach for predicting mechanical ventilation in patients with COVID-19.

BACKGROUND: Patients with coronavirus disease 2019 (COVID-19) requiring mechanical ventilation have ...

Multi-assignment clustering: Machine learning from a biological perspective.

A common approach for analyzing large-scale molecular data is to cluster objects sharing similar cha...

Continuous and automatic mortality risk prediction using vital signs in the intensive care unit: a hybrid neural network approach.

Mortality risk prediction can greatly improve the utilization of resources in intensive care units (...

M Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening From CT Imaging.

To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role ...

MS-CAM: Multi-Scale Class Activation Maps for Weakly-Supervised Segmentation of Geographic Atrophy Lesions in SD-OCT Images.

As one of the most critical characteristics in advanced stage of non-exudative Age-related Macular D...

Multi-objective regression test suite optimization using three variants of adaptive neuro fuzzy inference system.

In the process of software development, regression testing is one of the major activities that is do...

Transfer learning with chest X-rays for ER patient classification.

One of the challenges with urgent evaluation of patients with acute respiratory distress syndrome (A...

Predicting the need for intubation in the first 24 h after critical care admission using machine learning approaches.

Early and accurate prediction of the need for intubation may provide more time for preparation and i...

Development of machine learning models to predict RT-PCR results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patients with influenza-like symptoms using only basic clinical data.

BACKGROUND: Reverse Transcription-Polymerase Chain Reaction (RT-PCR) for Severe Acute Respiratory Sy...

Retrospective respiratory motion correction in cardiac cine MRI reconstruction using adversarial autoencoder and unsupervised learning.

The aim of this study was to develop a deep neural network for respiratory motion compensation in fr...

Direct Quantification of Coronary Artery Stenosis Through Hierarchical Attentive Multi-View Learning.

Quantification of coronary artery stenosis on X-ray angiography (XRA) images is of great importance ...

Conquering Data Variations in Resolution: A Slice-Aware Multi-Branch Decoder Network.

Fully convolutional neural networks have made promising progress in joint liver and liver tumor segm...