Cargando…

Machine learning-based suggestion for critical interventions in the management of potentially severe conditioned patients in emergency department triage

Providing timely intervention to critically ill patients is a challenging task in emergency departments (ED). Our study aimed to predict early critical interventions (CrIs), which can be used as clinical recommendations. This retrospective observational study was conducted in the ED of a tertiary ho...

Descripción completa

Detalles Bibliográficos
Autores principales:	Chang, Hansol, Yu, Jae Yong, Yoon, Sunyoung, Kim, Taerim, Cha, Won Chul
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218081/ https://www.ncbi.nlm.nih.gov/pubmed/35732641 http://dx.doi.org/10.1038/s41598-022-14422-4

Ejemplares similares

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)

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

Patient Anxiety and Communication Experience in the Emergency Department: A Mobile, Web-Based, Mixed-Methods Study on Patient Isolation During the COVID-19 Pandemic
por: Kim, Sumin, et al.
Publicado: (2023)

Clinical support system for triage based on federated learning for the Korea triage and acuity scale
por: Chang, Hansol, et al.
Publicado: (2023)

Intervention in the Timeliness of Two Electrocardiography Types for Patients in the Emergency Department With Chest Pain: Randomized Controlled Trial
por: Yoo, Suyoung, et al.
Publicado: (2022)

Feasibility of patch-type wireless 12-lead electrocardiogram in laypersons
por: Yoon, Sunyoung, et al.
Publicado: (2023)

Impact of COVID-19 Pandemic on the Overall Diagnostic and Therapeutic Process for Patients of Emergency Department and Those with Acute Cerebrovascular Disease
por: Chang, Hansol, et al.
Publicado: (2020)

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

A Real-Time Autonomous Dashboard for the Emergency Department: 5-Year Case Study
por: Yoo, Junsang, et al.
Publicado: (2018)

EARLY PREDICTION OF UNEXPECTED LATENT SHOCK IN THE EMERGENCY DEPARTMENT USING VITAL SIGNS
por: Chang, Hansol, et al.
Publicado: (2023)

Predicting 30-day mortality of patients with pneumonia in an emergency department setting using machine-learning models
por: Kang, Soo Yeon, et al.
Publicado: (2020)

Impact of the 24-hour time target policy for emergency departments in South Korea: a mixed method study in a single medical center
por: Park, Sookyung, et al.
Publicado: (2022)

User Experience of Mobile Personal Health Records for the Emergency Department: Mixed Methods Study
por: Kim, Su Min, et al.
Publicado: (2020)

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

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

Effect of the Automatic Needle Destroyer on Healthcare Providers’ Work in an Emergency Department: A Mixed-Methods Study
por: Kim, Su Min, et al.
Publicado: (2022)

Twelve-Lead Electrocardiogram Acquisition With a Patchy-Type Wireless Device in Ambulance Transport: Simulation-Based Randomized Controlled Trial
por: Yoon, Sunyoung, 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)

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

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)

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

Machine Learning–Based Prediction of Clinical Outcomes for Children During Emergency Department Triage
por: Goto, Tadahiro, et al.
Publicado: (2019)

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

Implementation of triage in a pediatric emergency department
por: Narayanan, Uma Priya, et al.
Publicado: (2014)

Are Pediatric Triage Systems Reliable in the Emergency Department?
por: Ebrahimi, Mohsen, et al.
Publicado: (2020)

Improving the wait time to triage at the emergency department
por: Shen, Yuzeng, et al.
Publicado: (2020)

Emergency department attendance after telephone triage
por: Gibson, Amy, et al.
Publicado: (2017)

Emergency department attendance after telephone triage
por: Denaxas, Spiros, et al.
Publicado: (2017)

Emergency department attendance after telephone triage
por: Ciminata, Giorgio, et al.
Publicado: (2017)

Accuracy of emergency department triage using the Emergency Severity Index and independent predictors of under-triage and over-triage in Brazil: a retrospective cohort analysis
por: Hinson, Jeremiah S., et al.
Publicado: (2018)

Epidemiologic trends of patients who visited nationwide emergency departments: a report from the National Emergency Department Information System (NEDIS) of Korea, 2018–2022
por: Yoo, Hyun Ho, et al.
Publicado: (2023)

Comparing complaint-based triage scales and early warning scores for emergency department triage
por: Schinkel, Michiel, et al.
Publicado: (2022)

A systematic review of triage-related interventions to improve patient flow in emergency departments
por: Oredsson, Sven, et al.
Publicado: (2011)

Swedish emergency department triage and interventions for improved patient flows: a national update
por: Farrokhnia, Nasim, et al.
Publicado: (2011)

Waiting Times in Emergency Department After Using the Emergency Severity Index Triage Tool
por: Mahmoodian, Farzad, et al.
Publicado: (2014)

Reversible cerebral vasoconstriction syndrome at the emergency department
por: Kim, Taerim, et al.
Publicado: (2015)

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)

Evaluating the effect of emergency department crowding on triage destination
por: O’Connor, Erin, et al.
Publicado: (2014)

Challenges and Opportunities for Emergency Department Sepsis Screening at Triage
por: Filbin, Michael R., et al.
Publicado: (2018)

Nurses in the triage of the emergency department: self-compassion and empathy
por: Savieto, Roberta Maria, et al.
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_h77k5jtp1mg3tsflldiq47far2