Critical Care

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

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A Real-Time Health 4.0 Framework with Novel Feature Extraction and Classification for Brain-Controlled IoT-Enabled Environments.

In this letter, we propose two novel methods for four-class motor imagery (MI) classification using ...

HetEnc: a deep learning predictive model for multi-type biological dataset.

BACKGROUND: Researchers today are generating unprecedented amounts of biological data. One trend in ...

Non-contact heart and respiratory rate monitoring of preterm infants based on a computer vision system: a method comparison study.

BACKGROUND: Non-contact heart rate (HR) and respiratory rate (RR) monitoring is necessary for preter...

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...

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...

Wearable IoT Smart-Log Patch: An Edge Computing-Based Bayesian Deep Learning Network System for Multi Access Physical Monitoring System.

According to the survey on various health centres, smart log-based multi access physical monitoring ...

Changes in clinical indicators related to the transition from dialysis to kidney transplantation-data from the ERA-EDTA Registry.

BACKGROUND: Kidney transplantation should improve abnormalities that are common during dialysis trea...

[Renal graft survival in patients transplanted from organs of deceased donors].

BACKGROUND: In Mexico, out of the total number of transplants it was reported, in 2014, a frequency ...

Mechanical Ventilation Guided by Electrical Impedance Tomography in Children With Acute Lung Injury.

OBJECTIVES: To provide proof-of-concept for a protocol applying a strategy of personalized mechanica...

Respiratory Sound Based Classification of Chronic Obstructive Pulmonary Disease: a Risk Stratification Approach in Machine Learning Paradigm.

This article investigates the classification of normal and COPD subjects on the basis of respiratory...

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...

Automatic Multi-Level In-Exhale Segmentation and Enhanced Generalized S-Transform for wheezing detection.

BACKGROUND AND OBJECTIVE: Wheezing is a common symptom of patients caused by asthma and chronic obst...

Object Detection During Newborn Resuscitation Activities.

OBJECTIVE: Birth asphyxia is a major newborn mortality problem in low-resource countries. Internatio...

A Multi-Sensor System for Silkworm Cocoon Gender Classification via Image Processing and Support Vector Machine.

Sericulture is traditionally a labor-intensive rural-based industry. In modern contexts, the develop...

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...

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