Critical Care

Comparison of machine learning models for the prediction of mortality of patients with unplanned extubation in intensive care units.

Unplanned extubation (UE) can be associated with fatal outcome; however, an accurate model for predi...

Vitamin D in the ICU: More sun for critically ill adult patients?

Critical illness in patients is characterized by systemic inflammation and oxidative stress. Vitamin...

Optimal intensive care outcome prediction over time using machine learning.

BACKGROUND: Prognostication is an essential tool for risk adjustment and decision making in the inte...

Non-directed bronchial lavage is a safe method for sampling the respiratory tract in critically ill patient.

Ventilated patients are at risk of acquiring ventilator-associated pneumonia. Various techniques are...

Development of an Artificial Intelligence Model to Guide the Management of Blood Pressure, Fluid Volume, and Dialysis Dose in End-Stage Kidney Disease Patients: Proof of Concept and First Clinical Assessment.

BACKGROUND: Fluid volume and blood pressure (BP) management are crucial endpoints for end-stage kidn...

Monitoring changes in distribution of pulmonary ventilation by functional electrical impedance tomography in anaesthetized ponies.

OBJECTIVE: To assess changes in the distribution in pulmonary ventilation in anaesthetized ponies us...

Blood Pressure Assessment with Differential Pulse Transit Time and Deep Learning: A Proof of Concept.

BACKGROUND: Modern clinical environments are laden with technology devices continuously gathering ph...

The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care.

Sepsis is the third leading cause of death worldwide and the main cause of mortality in hospitals, b...

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...

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...

Artificial Intelligence and Dialysis.

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...

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...

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...

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...

Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis.

In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain disease...