AIMC Topic: Critical Illness

Clear Filters Showing 131 to 140 of 188 articles

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

Journal of clinical monitoring and computing Sep 27, 2018
A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majority are difficult to identify even in a post-incident analysis. Changes in some patients' physiolog...
Infant, Newborn Reproducibility of Results Sensitivity and Specificity Infant Child, Preschool Humans Machine Learning Software Critical Illness Heart Arrest Signal Processing, Computer-Assisted Child Heart Rate Intensive Care Units, Pediatric Critical Care Monitoring, Physiologic Systole Blood Pressure Respiratory Rate Oxygen
View on PubMed DOI

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

Medicina intensiva Sep 20, 2018
INTRODUCTION: Sepsis is associated to a high mortality rate, and its severity must be evaluated quickly. The severity of illness scores used are intended to be applicable to all patient populations, and generally evaluate in-hospital mortality. Howev...
ROC Curve Models, Statistical Area Under Curve Humans Retrospective Studies Registries Machine Learning Critical Illness Algorithms Male Intensive Care Units Forecasting Middle Aged Female Severity of Illness Index Aged Sepsis Time Factors
View on PubMed DOI

Robotic technology provides objective and quantifiable metrics of neurocognitive functioning in survivors of critical illness:A feasibility study.

Journal of critical care Sep 12, 2018
PURPOSE: To assess the feasibility of using an integrated multimodal data collection strategy to characterize the post-intensive care syndrome (PICS).
Humans Robotics Feasibility Studies Survivors Executive Function Neurophysiological Monitoring Critical Illness Female Aged Male Middle Aged
View on PubMed DOI

Big data and machine learning in critical care: Opportunities for collaborative research.

Medicina intensiva Aug 2, 2018
The introduction of clinical information systems (CIS) in Intensive Care Units (ICUs) offers the possibility of storing a huge amount of machine-ready clinical data that can be used to improve patient outcomes and the allocation of resources, as well...
Databases, Factual Critical Illness Big Data Critical Care Spain Humans Machine Learning Interdisciplinary Research
View on PubMed DOI

Acute pain intensity monitoring with the classification of multiple physiological parameters.

Journal of clinical monitoring and computing Jun 26, 2018
Current acute pain intensity assessment tools are mainly based on self-reporting by patients, which is impractical for non-communicative, sedated or critically ill patients. In previous studies, various physiological signals have been observed qualit...
Hot Temperature Acute Pain Galvanic Skin Response Adult Male ROC Curve Monitoring, Physiologic Area Under Curve Pain Measurement Electromyography Heart Rate Healthy Volunteers Respiration Neural Networks, Computer Critical Illness Female Reproducibility of Results Young Adult Humans
View on PubMed DOI

Sentiment in nursing notes as an indicator of out-of-hospital mortality in intensive care patients.

PloS one Jun 7, 2018
BACKGROUND: Nursing notes have not been widely used in prediction models for clinical outcomes, despite containing rich information. Advances in natural language processing have made it possible to extract information from large scale unstructured da...
Natural Language Processing Kaplan-Meier Estimate Nursing Records Critical Care Nursing Intensive Care Units Humans Female Prognosis Aged Critical Illness Aged, 80 and over Young Adult Adult Male Middle Aged Adolescent Emotions
View on PubMed DOI

Using artificial intelligence to predict prolonged mechanical ventilation and tracheostomy placement.

The Journal of surgical research Apr 11, 2018
BACKGROUND: Early identification of critically ill patients who will require prolonged mechanical ventilation (PMV) has proven to be difficult. The purpose of this study was to use machine learning to identify patients at risk for PMV and tracheostom...
Supervised Machine Learning Patient Selection Critical Care Tracheostomy Databases, Factual Severity of Illness Index Critical Illness Length of Stay Intensive Care Units Time Factors Risk Assessment Treatment Outcome Respiration, Artificial Feasibility Studies Humans Decision Support Techniques
View on PubMed DOI

Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - a data-driven approach using machine-learning algorithms.

BMC pediatrics Mar 15, 2018
BACKGROUND: Since early antimicrobial therapy is mandatory in septic patients, immediate diagnosis and distinction from non-infectious SIRS is essential but hampered by the similarity of symptoms between both entities. We aimed to develop a diagnosti...
Machine Learning Algorithms Decision Support Techniques Prospective Studies Critical Illness Female Infant, Newborn Reproducibility of Results Humans Male Follow-Up Studies Infant Sepsis Diagnosis, Differential Adolescent Early Diagnosis Child, Preschool Child Systemic Inflammatory Response Syndrome
View on PubMed DOI

Population pharmacokinetics of continuous infusion of piperacillin in critically ill patients.

International journal of antimicrobial agents Dec 22, 2017
Dosing recommendations for continuous infusion of piperacillin, a broad-spectrum beta-lactam antibiotic, are mainly guided by outputs from population pharmacokinetic models constructed with intermittent infusion data. However, the probability of targ...
Sepsis Creatinine Anti-Bacterial Agents Humans Microbial Sensitivity Tests Piperacillin Pseudomonas aeruginosa Critical Illness Kidney Function Tests Tazobactam Pseudomonas Infections Female Drug Combinations Metabolic Clearance Rate Male Infusions, Intravenous Penicillanic Acid Middle Aged
View on PubMed DOI

High-Dose Vitamin D Administration Is Associated With Increases in Hemoglobin Concentrations in Mechanically Ventilated Critically Ill Adults: A Pilot Double-Blind, Randomized, Placebo-Controlled Trial.

JPEN. Journal of parenteral and enteral nutrition Dec 11, 2017
BACKGROUND: Anemia and vitamin D deficiency are highly prevalent in critical illness, and vitamin D status has been associated with hemoglobin concentrations in epidemiologic studies. We examined the effect of high-dose vitamin D therapy on hemoglobi...
Hepcidins Middle Aged Hemoglobins Humans Critical Care Critical Illness Respiration, Artificial Cholecalciferol Female Pilot Projects Aged Double-Blind Method Male Vitamins
View on PubMed DOI
Popular Topics
Recent Journals