Intensivists

Compressed sensing MRI via a multi-scale dilated residual convolution network.

Magnetic resonance imaging (MRI) reconstruction is an active inverse problem which can be addressed ...

Prodromal clinical, demographic, and socio-ecological correlates of asthma in adults: a 10-year statewide big data multi-domain analysis.

To identify prodromal correlates of asthma as compared to chronic obstructive pulmonary disease and...

Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction.

OBJECTIVE: The neonatal period of a child is considered the most crucial phase of its physical devel...

Automatic spondylolisthesis grading from MRIs across modalities using faster adversarial recognition network.

Grading spondylolisthesis into several stages from MRI images is challenging because detecting criti...

Novel drug-independent sedation level estimation based on machine learning of quantitative frontal electroencephalogram features in healthy volunteers.

BACKGROUND: Sedation indicators based on a single quantitative EEG (QEEG) feature have been criticis...

Designing minimal and scalable insect-inspired multi-locomotion millirobots.

In ant colonies, collectivity enables division of labour and resources with great scalability. Beyon...

A Deep Information Sharing Network for Multi-Contrast Compressed Sensing MRI Reconstruction.

Compressed sensing (CS) theory can accelerate multi-contrast magnetic resonance imaging (MRI) by sam...

AMC-Net: Asymmetric and multi-scale convolutional neural network for multi-label HPA classification.

BACKGROUND AND OBJECTIVES: The multi-label Human Protein Atlas (HPA) classification can yield a bett...

Block Forests: random forests for blocks of clinical and omics covariate data.

BACKGROUND: In the last years more and more multi-omics data are becoming available, that is, data f...

An intelligent warning model for early prediction of cardiac arrest in sepsis patients.

BACKGROUND: Sepsis-associated cardiac arrest is a common issue with the low survival rate. Early pre...

Modeling longitudinal imaging biomarkers with parametric Bayesian multi-task learning.

Longitudinal imaging biomarkers are invaluable for understanding the course of neurodegeneration, pr...

Multi-Class Neural Networks to Predict Lung Cancer.

Lung Cancer is the leading cause of death among all the cancers' in today's world. The survival rate...

Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning.

Currently, many critical care indices are not captured automatically at a granular level, rather are...

A multi-objective optimization approach for brain MRI segmentation using fuzzy entropy clustering and region-based active contour methods.

In this paper, we present a new multi-objective optimization approach for segmentation of Magnetic R...

Is artificial intelligence (AI) at the doorstep of Intensive Care Units (ICU) and operating room (OR)?

DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks.

Automated protein function prediction is critical for the annotation of uncharacterized protein sequ...

Using a Multi-Task Recurrent Neural Network With Attention Mechanisms to Predict Hospital Mortality of Patients.

Estimating hospital mortality of patients is important in assisting clinicians to make decisions and...

A machine learning approach for predicting urine output after fluid administration.

BACKGROUND AND OBJECTIVE: To develop a machine learning model to predict urine output (UO) in sepsis...

Prediction of binding property of RNA-binding proteins using multi-sized filters and multi-modal deep convolutional neural network.

RNA-binding proteins (RBPs) are important in gene expression regulations by post-transcriptional con...

Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs.

OBJECTIVE: Sepsis remains a costly and prevalent syndrome in hospitals; however, machine learning sy...

Refining humane endpoints in mouse models of disease by systematic review and machine learning-based endpoint definition.

Ideally, humane endpoints allow for early termination of experiments by minimizing an animal's disco...