Intensivists

Comparative outcomes of robot-assisted minimally invasive versus open esophagectomy in patients with esophageal squamous cell carcinoma: a propensity score-weighted analysis.

Robots are increasingly used in minimally invasive surgery. We evaluated the clinical benefits of ro...

Prediction of an Acute Hypotensive Episode During an ICU Hospitalization With a Super Learner Machine-Learning Algorithm.

BACKGROUND: Acute hypotensive episodes (AHE), defined as a drop in the mean arterial pressure (MAP) ...

Acceptability and Perceived Utility of Telemedical Consultation during Cardiac Arrest Resuscitation. A Multicenter Survey.

Many clinicians who participate in or lead in-hospital cardiac arrest (IHCA) resuscitations lack co...

[Prognostic model of small sample critical diseases based on transfer learning].

Aiming at the problem that the small samples of critical disease in clinic may lead to prognostic mo...

Assessing clinical heterogeneity in sepsis through treatment patterns and machine learning.

OBJECTIVE: To use unsupervised topic modeling to evaluate heterogeneity in sepsis treatment patterns...

Respiratory parameters and acute kidney injury in acute respiratory distress syndrome: a causal inference study.

BACKGROUND: Assess the respiratory-related parameters associated with subsequent severe acute kidney...

Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

OBJECTIVE: To assess clinician perceptions of a machine learning-based early warning system to predi...

A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.

OBJECTIVES: Develop and implement a machine learning algorithm to predict severe sepsis and septic s...

A Double-Blind, Randomized Control Trial of Rapidly Infused High Strong Ion Difference (SID) Fluid Versus Hartmann's Solution on Acid-Base Status in Sepsis Patients in the Emergency Department.

BACKGROUND: Balanced fluids are preferred in initial resuscitation of septic patients based on sever...

Development of a Machine Learning Model Predicting an ICU Admission for Patients with Elective Surgery and Its Prospective Validation in Clinical Practice.

Frequent utilization of the Intensive Care Unit (ICU) is associated with higher costs and decreased ...

Comparing Machine Learning Algorithms for Predicting Acute Kidney Injury.

Prior studies have used vital signs and laboratory measurements with conventional modeling technique...

What every intensivist should know about Big Data and targeted machine learning in the intensive care unit.

Dynamic Features Impact on the Quality of Chronic Heart Failure Predictive Modelling.

We study the way dynamics affects modelling in chronic heart failure (CHF) tasks. By dynamics we und...

Hydrocortisone, Vitamin C and thiamine for the treatment of sepsis and septic shock following cardiac surgery.

BACKGROUND AND AIMS: The effect of vitamin C on vasopressor requirement in critically ill patients h...

Effects of Midazolam and Midazolam-Butorphanol on Gastrointestinal Transit Time and Motility in Cockatiels ().

Positive contrast gastrointestinal (GI) studies are performed frequently in avian medicine to identi...

The role of presepsin in the diagnosis and assessment of severity of sepsis and severe pneumonia.

AIM: The aim of this study was to evaluate marker of inflammation presepsin to improve diagnosis of ...

Applying Artificial Intelligence to Identify Physiomarkers Predicting Severe Sepsis in the PICU.

OBJECTIVES: We used artificial intelligence to develop a novel algorithm using physiomarkers to pred...

Inclusion of Unstructured Clinical Text Improves Early Prediction of Death or Prolonged ICU Stay.

OBJECTIVES: Early prediction of undesired outcomes among newly hospitalized patients could improve p...

Evaluating ICU Clinical Severity Scoring Systems and Machine Learning Applications: APACHE IV/IVa Case Study.

Clinical scoring systems have been developed for many specific applications, yet they remain underut...

Development and Evaluation of an Automated Machine Learning Algorithm for In-Hospital Mortality Risk Adjustment Among Critical Care Patients.

OBJECTIVES: Risk adjustment algorithms for ICU mortality are necessary for measuring and improving I...

[Application of support vector machine in predicting in-hospital mortality risk of patients with acute kidney injury in ICU].

OBJECTIVE: To construct an in-hospital mortality prediction model for patients with acute kidney inj...