Cargando…

Prediction of Cardiac Arrest in the Emergency Department Based on Machine Learning and Sequential Characteristics: Model Development and Retrospective Clinical Validation Study

BACKGROUND: The development and application of clinical prediction models using machine learning in clinical decision support systems is attracting increasing attention. OBJECTIVE: The aims of this study were to develop a prediction model for cardiac arrest in the emergency department (ED) using mac...

Descripción completa

Detalles Bibliográficos
Autores principales:	Hong, Sungjun, Lee, Sungjoo, Lee, Jeonghoon, Cha, Won Chul, Kim, Kyunga
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	JMIR Publications 2020
Materias:	Original Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435618/ https://www.ncbi.nlm.nih.gov/pubmed/32749227 http://dx.doi.org/10.2196/15932

Ejemplares similares

Predicting Adverse Outcomes for Febrile Patients in the Emergency Department Using Sparse Laboratory Data: Development of a Time Adaptive Model
por: Lee, Sungjoo, et al.
Publicado: (2020)

Predicting cardiac arrest in the emergency department
por: Mitchell, Oscar J.L., et al.
Publicado: (2020)

External validation of a triage tool for predicting cardiac arrest in the emergency department
por: Sun, Jen-Tang, et al.
Publicado: (2022)

Alert Override Patterns With a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study
por: Yoo, Junsang, et al.
Publicado: (2020)

Development and Validation of a Novel Triage Tool for Predicting Cardiac Arrest in the Emergency Department
por: Tsai, Chu-Lin, et al.
Publicado: (2022)

Beyond Advanced Cardiac Life Support: Dual-sequential Defibrillation for Refractory Ventricular Fibrillation after Witnessed Cardiac Arrest in the Emergency Department
por: Frye, Kenneth L, et al.
Publicado: (2018)

Reduction of in-hospital cardiac arrest with sequential deployment of rapid response team and medical emergency team to the emergency department and acute care wards
por: Mankidy, Babith, et al.
Publicado: (2020)

Frequent Mobile Electronic Medical Records Users Respond More Quickly to Emergency Department Consultation Requests: Retrospective Quantitative Study
por: Jung, Kwang Yul, et al.
Publicado: (2020)

An external validation study of the Score for Emergency Risk Prediction (SERP), an interpretable machine learning-based triage score for the emergency department
por: Yu, Jae Yong, et al.
Publicado: (2022)

Serum Lactate for Predicting Cardiac Arrest in the Emergency Department
por: Hsu, Shu-Hsien, et al.
Publicado: (2022)

Correction: Frequent Mobile Electronic Medical Records Users Respond More Quickly to Emergency Department Consultation Requests: Retrospective Quantitative Study
por: Jung, Kwang Yul, et al.
Publicado: (2022)

Maximum emergency department overcrowding is correlated with occurrence of unexpected cardiac arrest
por: Kim, June-sung, et al.
Publicado: (2020)

Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Retrospective, Comparative, Machine Learning Study
por: Hur, Sujeong, et al.
Publicado: (2021)

Feasibility of focused cardiac ultrasound during cardiac arrest in the emergency department
por: Balderston, Jessica R., et al.
Publicado: (2021)

Factors Associated with the Occurrence of Cardiac Arrest after Emergency Tracheal Intubation in the Emergency Department
por: Kim, Won Young, et al.
Publicado: (2014)

Ionized calcium level at emergency department arrival is associated with return of spontaneous circulation in out-of-hospital cardiac arrest
por: Kim, Sun Ju, et al.
Publicado: (2020)

Association between Shock Index and Emergency Department Cardiac Arrest
por: Chen, Chao-Tung, et al.
Publicado: (2021)

Correction to: Maximum emergency department overcrowding is correlated with occurrence of unexpected cardiac arrest
por: Kim, June-sung, et al.
Publicado: (2020)

Experience of extracorporeal cardiopulmonary resuscitation in a refractory cardiac arrest patient at the emergency department
por: Han, Kap Su, et al.
Publicado: (2019)

Resuscitation duration inequality by patient characteristics in emergency department out-of-hospital cardiac arrest: an observational study
por: Kang, Minoo, et al.
Publicado: (2014)

Machine Learning and Initial Nursing Assessment-Based Triage System for Emergency Department
por: Yu, Jae Yong, et al.
Publicado: (2020)

Artificial intelligence decision points in an emergency department
por: Chang, Hansol, et al.
Publicado: (2022)

Traumatic cardiac arrest in the emergency department– Overview upon primary causes
por: Georgescu, V, et al.
Publicado: (2014)

Pediatric cardiac arrest in the emergency department: Outcome is related to the time of admission
por: Yurtseven, Ali, et al.
Publicado: (2019)

Pregnancy With Cardiac Arrest in the Emergency Department: Case Report With Review of Literature
por: R, Gunaseelan, et al.
Publicado: (2021)

In-Hospital Cardiac Arrest in United States Emergency Departments, 2010–2018
por: Sung, Chih-Wei, et al.
Publicado: (2022)

Clinical Survey and Predictors of Outcomes of Pediatric Out-of-Hospital Cardiac Arrest Admitted to the Emergency Department
por: Lee, Jung, et al.
Publicado: (2019)

Emergency Department Overcrowding and Ambulance Turnaround Time
por: Lee, Yu Jin, et al.
Publicado: (2015)

Developing a Time-Adaptive Prediction Model for Out-of-Hospital Cardiac Arrest: Nationwide Cohort Study in Korea
por: Kim, Ji Woong, et al.
Publicado: (2021)

Cardiac Arrest Survival Postresuscitation In-Hospital (CASPRI) Score Predicts Neurological Favorable Survival in Emergency Department Cardiac Arrest
por: Tsai, Jeffrey Che-Hung, et al.
Publicado: (2021)

A Retrospective Study: Quick Scoring of Symptoms to Estimate the Risk of Cardiac Arrest in the Emergency Department
por: Xu, Yaoke, et al.
Publicado: (2022)

Predictors of survival following extracorporeal cardiopulmonary resuscitation in patients with acute myocardial infarction-complicated refractory cardiac arrest in the emergency department: a retrospective study
por: Han, Sang Jin, et al.
Publicado: (2015)

A Novel High-Speed Resonant Frequency Tracking Method Using Transient Characteristics in a Piezoelectric Transducer
por: Moon, Jeonghoon, et al.
Publicado: (2022)

Impact of Coronavirus Disease 2019 Pandemic on Pediatric Out-of-Hospital Cardiac Arrest in the Emergency Department
por: Chen, Chun-Yu, et al.
Publicado: (2022)

Machine learning-based suggestion for critical interventions in the management of potentially severe conditioned patients in emergency department triage
por: Chang, Hansol, et al.
Publicado: (2022)

Development of a machine-learning algorithm to predict in-hospital cardiac arrest for emergency department patients using a nationwide database
por: Kim, Ji Hoon, et al.
Publicado: (2022)

New Termination-of-Resuscitation Models and Prognostication in Out-of-Hospital Cardiac Arrest Using Electrocardiogram Rhythms Documented in the Field and the Emergency Department
por: Lee, Dong Eun, et al.
Publicado: (2019)

Out-of-hospital cardiac arrests in Switzerland: Predictors for emergency department mortality in patients with ROSC or on-going CPR on admission to the emergency department
por: Sauter, Thomas C., et al.
Publicado: (2017)

Diagnostic and therapeutic characteristics of diabetes mellitus and risk of out-of-hospital cardiac arrest
por: Park, Jeong Ho, et al.
Publicado: (2022)

Best Practices in Managing Cardiac Arrest in the Emergency Department During the COVID-19 Pandemic
por: Heaton, Heather A., et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_3h6754s2av5fm1og299a3jvfd0