Critical Care

Comparisons of Pressure-controlled Ventilation with Volume Guarantee and Volume-controlled 1:1 Equal Ratio Ventilation on Oxygenation and Respiratory Mechanics during Robot-assisted Laparoscopic Radical Prostatectomy: a Randomized-controlled Trial.

During robot-assisted laparoscopic radical prostatectomy (RALP), steep Trendelenburg position and c...

Big data and targeted machine learning in action to assist medical decision in the ICU.

Historically, personalised medicine has been synonymous with pharmacogenomics and oncology. We argue...

Minimally invasive, robot-assisted procedure for kidney transplantation among morbidly obese: Positive outcomes at 5 years post-transplant.

The pre-transplant weight loss required of end-stage renal disease patients is often unachievable. T...

Multi-Channel Convolutional Neural Networks Architecture Feeding for Effective EEG Mental Tasks Classification.

Mental tasks classification is increasingly recognized as a major challenge in the field of EEG sign...

Analysis of platelet-activating factors in severe sepsis by flow cytometry and its correlation with clinical sepsis scoring system: A pilot study.

BACKGROUND: Sepsis is a major global healthcare concern. Platelets and leucocytes play a key role in...

Progress in the Development and Challenges for the Use of Artificial Kidneys and Wearable Dialysis Devices.

BACKGROUND: Renal transplantation is the treatment of choice for chronic kidney disease (CKD) patien...

Using machine learning to guide targeted and locally-tailored empiric antibiotic prescribing in a children's hospital in Cambodia.

: Early and appropriate empiric antibiotic treatment of patients suspected of having sepsis is assoc...

Infant Brain Development Prediction With Latent Partial Multi-View Representation Learning.

The early postnatal period witnesses rapid and dynamic brain development. However, the relationship ...

Changes of Early Sepsis Biomarker Presepsin Level during Hemodialysis: Influence of β-Microglobulin Clearance of Dialysis Membrane: A Preliminary Study.

BACKGROUND: Although presepsin (P-SEP) is an early sepsis biomarker, sepsis is often suspected after...

Artificial Intelligence and Dialysis.

Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks.

Missing data is a ubiquitous problem. It is especially challenging in medical settings because many ...

Early Expression Detection via Online Multi-Instance Learning With Nonlinear Extension.

Video-based facial expression recognition has received substantial attention over the past decade, w...

Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.

A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the ca...

Multi-dimensional proprio-proximus machine learning for assessment of myocardial infarction.

This work presents a novel analysis methodology that utilises high-resolution, multi-dimensional inf...

Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification.

Effective utilization of multi-center data for autism spectrum disorder (ASD) diagnosis recently has...

Multi-task SonoEyeNet: Detection of Fetal Standardized Planes Assisted by Generated Sonographer Attention Maps.

We present a novel multi-task convolutional neural network called Multi-task SonoEyeNet () that lear...

Automatic Age Estimation and Majority Age Classification From Multi-Factorial MRI Data.

Age estimation from radiologic data is an important topic both in clinical medicine as well as in fo...

Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony.

BACKGROUND: As healthcare increasingly digitizes, streaming waveform data is being made available fr...

A machine learning-based model for 1-year mortality prediction in patients admitted to an Intensive Care Unit with a diagnosis of sepsis.

INTRODUCTION: Sepsis is associated to a high mortality rate, and its severity must be evaluated quic...

Cost-sensitive multi-label learning with positive and negative label pairwise correlations.

Multi-label learning is the problem where each instance is associated with multiple labels simultane...

Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study.

BACKGROUND: Based on international diagnostic guidelines, high-resolution CT plays a central part in...