Critical Care

A minimal set of physiomarkers in continuous high frequency data streams predict adult sepsis onset earlier.

PURPOSE: Sepsis is a life-threatening condition with high mortality rates and expensive treatment costs. To improve short- and long-term outcomes, it is critical to detect at-risk sepsis patients at an early stage.

Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits.

Multi-trait and multi-environment data are common in animal and plant breeding programs. However, what is lacking are more powerful statistical models that can exploit the correlation between traits to improve prediction accuracy in the context of genomic selection (GS). Multi-trait models are more complex than univariate models and usually require more computational resources, but they are prefer...

Association Between Early Intravenous Fluids Provided by Paramedics and Subsequent In-Hospital Mortality Among Patients With Sepsis.

IMPORTANCE: Early administration of intravenous fluids is recommended for all patients with sepsis, but the association of this treatment with mortali...

Validation of Prediction Models for Critical Care Outcomes Using Natural Language Processing of Electronic Health Record Data.

IMPORTANCE: Accurate prediction of outcomes among patients in intensive care units (ICUs) is important for clinical research and monitoring care quali...

Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning.

Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because individual patients respond differently to treatment. Thus, t...

A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.

Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objectiv...

An Interpretable ICU Mortality Prediction Model Based on Logistic Regression and Recurrent Neural Networks with LSTM units.

Most existing studies used logistic regression to establish scoring systems to predict intensive care unit (ICU) mortality. Machine learning-based app...

A Unique Case of Severe Anemia Secondary to Copper Deficiency in an Adult Patient.

Anemia is a frequently encountered problem in the healthcare system. Common causes of anemia include blood loss, followed by impaired red blood cell p...

Machine Learning Algorithms Utilizing Functional Respiratory Imaging May Predict COPD Exacerbations.

RATIONALE AND OBJECTIVES: Acute chronic obstructive pulmonary disease exacerbations (AECOPD) have a significant negative impact on the quality of life...

Machine learning in critical care: state-of-the-art and a sepsis case study.

BACKGROUND: Like other scientific fields, such as cosmology, high-energy physics, or even the life sciences, medicine and healthcare face the challeng...

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 predicting the mortality of UE patients in intensive ca...

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 D has a myriad of biological functions relevant t...

Optimal intensive care outcome prediction over time using machine learning.

BACKGROUND: Prognostication is an essential tool for risk adjustment and decision making in the intensive care unit (ICU). Research into prognosticati...

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 available for diagnosing ventilator-associated pn...

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 kidney disease patients. BP control in clinical practi...

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 using electrical impedance tomography (EIT).

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 physiological data from patients. This is especially...

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, but the best treatment strategy remains uncertain. ...

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 carbon dioxide pneumoperitoneum are inevitable for ...

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 for a new framework for personalised medicine ana...