AIMC Topic: Heart Arrest

Clear Filters Showing 41 to 50 of 78 articles

Development and validation of a deep-learning-based pediatric early warning system: A single-center study.

Biomedical journal Jan 18, 2021
BACKGROUND: Early detection and prompt intervention for clinically deteriorating events are needed to improve clinical outcomes. There have been several attempts at this, including the introduction of rapid response teams (RRTs) with early warning sc...
Deep Learning Child Intensive Care Units, Pediatric ROC Curve Heart Arrest Humans Retrospective Studies
View on PubMed DOI

Artificial intelligence algorithm for predicting cardiac arrest using electrocardiography.

Scandinavian journal of trauma, resuscitation and emergency medicine Oct 6, 2020
BACKGROUND: In-hospital cardiac arrest is a major burden in health care. Although several track-and-trigger systems are used to predict cardiac arrest, they often have unsatisfactory performances. We hypothesized that a deep-learning-based artificial...
Aged Male Middle Aged Deep Learning Electrocardiography Humans Patient Transfer Algorithms Retrospective Studies Heart Arrest Intensive Care Units Female Hospitalization
View on PubMed DOI

Outcome prediction with resting-state functional connectivity after cardiac arrest.

Scientific reports Jul 16, 2020
Predicting outcome in comatose patients after successful cardiopulmonary resuscitation is challenging. Our primary aim was to assess the potential contribution of resting-state-functional magnetic resonance imaging (RS-fMRI) in predicting neurologica...
Machine Learning Prospective Studies Prognosis Clinical Decision-Making Female Humans Consciousness Neural Pathways Nerve Net Thalamus Cardiopulmonary Resuscitation Heart Arrest Coma Male Aged Middle Aged Aged, 80 and over Young Adult Adolescent Adult Magnetic Resonance Imaging Brain Mapping
View on PubMed DOI

Value of laboratory results in addition to vital signs in a machine learning algorithm to predict in-hospital cardiac arrest: A single-center retrospective cohort study.

PloS one Jul 13, 2020
BACKGROUND: Although machine learning-based prediction models for in-hospital cardiac arrest (IHCA) have been widely investigated, it is unknown whether a model based on vital signs alone (Vitals-Only model) can perform similarly to a model that cons...
Hospitalization Aged Male Middle Aged Vital Signs Heart Arrest Humans Machine Learning Prognosis Retrospective Studies Female
View on PubMed DOI

Resting-State Brain Activity for Early Prediction Outcome in Postanoxic Patients in a Coma with Indeterminate Clinical Prognosis.

AJNR. American journal of neuroradiology May 21, 2020
BACKGROUND AND PURPOSE: Early outcome prediction of postanoxic patients in a coma after cardiac arrest proves challenging. Current prognostication relies on multimodal testing, using clinical examination, electrophysiologic testing, biomarkers, and s...
Male Middle Aged Support Vector Machine Magnetic Resonance Imaging Recovery of Function Prognosis Female Aged Adult Hypoxia Heart Arrest Coma Humans Prospective Studies Brain
View on PubMed DOI

An intelligent warning model for early prediction of cardiac arrest in sepsis patients.

Computer methods and programs in biomedicine Jun 11, 2019
BACKGROUND: Sepsis-associated cardiac arrest is a common issue with the low survival rate. Early prediction of cardiac arrest can provide the time required for intervening and preventing its onset in order to reduce mortality. Several studies have be...
Humans Multivariate Analysis Vital Signs Normal Distribution Heart Arrest Middle Aged Severity of Illness Index Case-Control Studies Sepsis Adolescent Incidence Decision Trees Monitoring, Ambulatory APACHE Reproducibility of Results Machine Learning Young Adult Algorithms Adult Electronic Health Records Sensitivity and Specificity Female Male
View on PubMed DOI

Developing neural network models for early detection of cardiac arrest in emergency department.

The American journal of emergency medicine Apr 7, 2019
BACKGROUND: Automated surveillance for cardiac arrests would be useful in overcrowded emergency departments. The purpose of this study is to develop and test artificial neural network (ANN) classifiers for early detection of patients at risk of cardi...
Male Middle Aged ROC Curve Logistic Models Predictive Value of Tests Emergency Service, Hospital Early Diagnosis Heart Arrest Retrospective Studies Electronic Health Records Female Aged Adult Humans Neural Networks, Computer
View on PubMed DOI

Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study.

PLoS medicine Nov 30, 2018
BACKGROUND: Resuscitated cardiac arrest is associated with high mortality; however, the ability to estimate risk of adverse outcomes using existing illness severity scores is limited. Using in-hospital data available within the first 24 hours of admi...
Cardiopulmonary Resuscitation Heart Arrest Clinical Decision-Making Female Risk Factors Treatment Outcome Aged Machine Learning Health Status Humans Male Middle Aged Decision Support Techniques Australia Databases, Factual Risk Assessment Registries Retrospective Studies Time Factors New Zealand Hospital Mortality
View on PubMed DOI

A Machine Learning Shock Decision Algorithm for Use During Piston-Driven Chest Compressions.

IEEE transactions on bio-medical engineering Oct 31, 2018
GOAL: Accurate shock decision methods during piston-driven cardiopulmonary resuscitation (CPR) would contribute to improve therapy and increase cardiac arrest survival rates. The best current methods are computationally demanding, and their accuracy ...
Humans Support Vector Machine Decision Support Systems, Clinical Wavelet Analysis Electrocardiography Cardiopulmonary Resuscitation Heart Arrest
View on PubMed DOI

Toward analyzing and synthesizing previous research in early prediction of cardiac arrest using machine learning based on a multi-layered integrative framework.

Journal of biomedical informatics Oct 30, 2018
BACKGROUND: One of the significant problems in the field of healthcare is the low survival rate of people who have experienced sudden cardiac arrest. Early prediction of cardiac arrest can provide the time required for intervening and preventing its ...
Heart Arrest Reproducibility of Results Humans Support Vector Machine Algorithms Decision Making Databases, Factual Medical Informatics Research Proportional Hazards Models
View on PubMed DOI
Popular Topics
Recent Journals