Cargando…

Machine Learning–Based Prediction of Clinical Outcomes for Children During Emergency Department Triage

IMPORTANCE: While machine learning approaches may enhance prediction ability, little is known about their utility in emergency department (ED) triage. OBJECTIVES: To examine the performance of machine learning approaches to predict clinical outcomes and disposition in children in the ED and to compa...

Descripción completa

Detalles Bibliográficos
Autores principales:	Goto, Tadahiro, Camargo, Carlos A., Faridi, Mohammad Kamal, Freishtat, Robert J., Hasegawa, Kohei
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	American Medical Association 2019
Materias:	Original Investigation
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6484561/ https://www.ncbi.nlm.nih.gov/pubmed/30646206 http://dx.doi.org/10.1001/jamanetworkopen.2018.6937

Ejemplares similares

Emergency department triage prediction of clinical outcomes using machine learning models
por: Raita, Yoshihiko, et al.
Publicado: (2019)

Emergency Department Utilization by Children in the USA, 2010–2011
por: Goto, Tadahiro, et al.
Publicado: (2017)

The association of aspirin use with severity of acute exacerbation of chronic obstructive pulmonary disease: a retrospective cohort study
por: Goto, Tadahiro, et al.
Publicado: (2018)

Contribution of social factors to readmissions within 30 days after hospitalization for COPD exacerbation
por: Goto, Tadahiro, et al.
Publicado: (2020)

Machine Learning Approaches for Predicting Difficult Airway and First-Pass Success in the Emergency Department: Multicenter Prospective Observational Study
por: Yamanaka, Syunsuke, et al.
Publicado: (2022)

Predicting hospital admission at emergency department triage using machine learning
por: Hong, Woo Suk, et al.
Publicado: (2018)

Association of Obesity With Severity of Heart Failure Exacerbation: A Population‐Based Study
por: Hirayama, Atsushi, et al.
Publicado: (2018)

Race and Ethnicity and Primary Language in Emergency Department Triage
por: Joseph, Joshua W., et al.
Publicado: (2023)

Triage of children in an Emergency Department
por: Graversen, Dennis, et al.
Publicado: (2013)

Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions
por: Xie, Feng, et al.
Publicado: (2021)

Machine Learning-Based Prediction of Korean Triage and Acuity Scale Level in Emergency Department Patients
por: Choi, Sae Won, et al.
Publicado: (2019)

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

Demographics and Outcomes of Pulmonary Hypertension Patients in United States Emergency Departments
por: Wilcox, Susan R., et al.
Publicado: (2020)

Use of Machine Learning to Differentiate Children With Kawasaki Disease From Other Febrile Children in a Pediatric Emergency Department
por: Tsai, Chih-Min, et al.
Publicado: (2023)

Medical emergency department triage data processing using a machine-learning solution
por: Vântu, Andreea, et al.
Publicado: (2023)

Triage nurse prediction as a covariate in a machine learning prediction algorithm for hospital admission from the emergency department
por: Afnan, Michael Anis Mihdi, et al.
Publicado: (2021)

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)

Association of Number of Physician Postgraduate Years With Patient Intubation Outcomes in the Emergency Department
por: Goto, Tadahiro, et al.
Publicado: (2022)

Near-universal hospitalization of US emergency department patients with cancer and febrile neutropenia
por: Baugh, Christopher W., et al.
Publicado: (2019)

Factors associated with successful rescue intubation attempts in the emergency department: an analysis of multicenter prospective observational study in Japan
por: Goto, Yukari, et al.
Publicado: (2019)

Methylxanthine use for acute asthma in the emergency department in Japan: a multicenter observational study
por: Morikawa, Miki, et al.
Publicado: (2019)

Fractional exhaled nitric oxide levels in asthma–COPD overlap syndrome: analysis of the National Health and Nutrition Examination Survey, 2007–2012
por: Goto, Tadahiro, et al.
Publicado: (2016)

A Prehospital Triage System to Detect Traumatic Intracranial Hemorrhage Using Machine Learning Algorithms
por: Abe, Daisu, et al.
Publicado: (2022)

The incidence of post-intubation hypertension and association with repeated intubation attempts in the emergency department
por: Inoue, Akihiko, et al.
Publicado: (2019)

Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning
por: Horng, Steven, et al.
Publicado: (2017)

Airway management in the pediatric emergency department in Japan: A multicenter prospective observational study
por: Hagiwara, Yusuke, et al.
Publicado: (2022)

Factors Associated with First-Pass Success in Pediatric Intubation in the Emergency Department
por: Goto, Tadahiro, et al.
Publicado: (2016)

Emergency department triage: an ethical analysis
por: Aacharya, Ramesh P, et al.
Publicado: (2011)

Association of ketamine use with lower risks of post-intubation hypotension in hemodynamically-unstable patients in the emergency department
por: Ishimaru, Tadayoshi, et al.
Publicado: (2019)

First-Pass Success of Video Laryngoscope Compared With Direct Laryngoscope in Intubations Performed by Residents in the Emergency Department
por: Sugaya, Akihiko, et al.
Publicado: (2023)

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)

Using Machine Learning to Predict Bacteremia in Febrile Children Presented to the Emergency Department
por: Tsai, Chih-Min, et al.
Publicado: (2020)

Machine learning-based prediction of critical illness in children visiting the emergency department
por: Hwang, Soyun, et al.
Publicado: (2022)

Author Correction: Association of ketamine use with lower risks of post-intubation hypotension in hemodynamically-unstable patients in the emergency department
por: Ishimaru, Tadayoshi, et al.
Publicado: (2020)

Machine learning models predicting undertriage in telephone triage
por: Inokuchi, Ryota, et al.
Publicado: (2022)

Association of airway obstruction with first-pass success and intubation-related adverse events in the emergency department: multicenter prospective observational studies
por: Takahashi, Jin, et al.
Publicado: (2023)

Development and validation of a practical machine-learning triage algorithm for the detection of patients in need of critical care in the emergency department
por: Liu, Yecheng, et al.
Publicado: (2021)

Machine learning–based triage to identify low-severity patients with a short discharge length of stay in emergency department
por: Chang, Yu-Hsin, et al.
Publicado: (2022)

The Accuracy of Sepsis Screening Score for Mortality Prediction at Emergency Department Triage
por: Suttapanit, Karn, et al.
Publicado: (2022)

Associations of obesity with tracheal intubation success on first attempt and adverse events in the emergency department: An analysis of the multicenter prospective observational study in Japan
por: Yakushiji, Hiromasa, et al.
Publicado: (2018)

Cannot write session to /tmp/vufind_sessions/sess_19945d93radmdjd0u6fq63bhu3