Cargando…

Using Machine Learning to Predict ICU Transfer in Hospitalized COVID-19 Patients

Objectives: Approximately 20–30% of patients with COVID-19 require hospitalization, and 5–12% may require critical care in an intensive care unit (ICU). A rapid surge in cases of severe COVID-19 will lead to a corresponding surge in demand for ICU care. Because of constraints on resources, frontline...

Descripción completa

Detalles Bibliográficos
Autores principales:	Cheng, Fu-Yuan, Joshi, Himanshu, Tandon, Pranai, Freeman, Robert, Reich, David L, Mazumdar, Madhu, Kohli-Seth, Roopa, Levin, Matthew A., Timsina, Prem, Kia, Arash
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2020
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7356638/ https://www.ncbi.nlm.nih.gov/pubmed/32492874 http://dx.doi.org/10.3390/jcm9061668

Ejemplares similares

MEWS++: Enhancing the Prediction of Clinical Deterioration in Admitted Patients through a Machine Learning Model
por: Kia, Arash, et al.
Publicado: (2020)

A Hybrid Decision Tree and Deep Learning Approach Combining Medical Imaging and Electronic Medical Records to Predict Intubation Among Hospitalized Patients With COVID-19: Algorithm Development and Validation
por: Nguyen, Kim-Anh-Nhi, et al.
Publicado: (2023)

Implementing a Machine Learning Screening Tool for Malnutrition: Insights From Qualitative Research Applicable to Other Machine Learning–Based Clinical Decision Support Systems
por: Besculides, Melanie, et al.
Publicado: (2023)

Predicting Adult Hospital Admission from Emergency Department Using Machine Learning: An Inclusive Gradient Boosting Model
por: Patel, Dhavalkumar, et al.
Publicado: (2022)

The fourth wave: vaccination status and intensive care unit mortality at a large hospital system in New York City
por: Tandon, Pranai, et al.
Publicado: (2022)

Comparing Seasonal Trends in Coronavirus Disease 2019 Patient Data at a Quaternary Hospital in New York City
por: Tandon, Pranai, et al.
Publicado: (2021)

The Third Wave: Comparing Seasonal Trends in COVID-19 Patient Data at a Large Hospital System in New York City
por: Tandon, Pranai, et al.
Publicado: (2022)

Predicting adult neuroscience intensive care unit admission from emergency department triage using a retrospective, tabular-free text machine learning approach
por: Klang, Eyal, et al.
Publicado: (2021)

Timing of Intubation and In-Hospital Mortality in Patients With Coronavirus Disease 2019
por: Hyman, Jaime B., et al.
Publicado: (2020)

Impact of Myocardial Injury in Hospitalized Patients With COVID-19 in 2 Peak Time Periods
por: Bienstock, Solomon W., et al.
Publicado: (2021)

The Mount Sinai Hospital Institute for critical care medicine response to the COVID-19 pandemic
por: Wang, Jennifer, et al.
Publicado: (2021)

Anticoagulation, Bleeding, Mortality, and Pathology in Hospitalized Patients With COVID-19
por: Nadkarni, Girish N., et al.
Publicado: (2020)

On classifying sepsis heterogeneity in the ICU: insight using machine learning
por: Ibrahim, Zina M, et al.
Publicado: (2020)

Predicting open wound mortality in the ICU using machine learning
por: Akiki, Ronald K., et al.
Publicado: (2021)

Predicting Prolonged Length of ICU Stay through Machine Learning
por: Wu, Jingyi, et al.
Publicado: (2021)

Machine learning-based prediction of in-ICU mortality in pneumonia patients
por: Jeon, Eun-Tae, et al.
Publicado: (2023)

Prediction of ICU Patients’ Deterioration Using Machine Learning Techniques
por: Aldhoayan, Mohammed D, et al.
Publicado: (2023)

Machine learning to predict in‐hospital mortality among patients with severe obesity: Proof of concept study
por: Soffer, Shelly, et al.
Publicado: (2022)

A Machine Learning Model for Accurate Prediction of Sepsis in ICU Patients
por: Wang, Dong, et al.
Publicado: (2021)

Predicting the Mortality of ICU Patients by Topic Model with Machine-Learning Techniques
por: Chiu, Chih-Chou, et al.
Publicado: (2022)

Prediction algorithm for ICU mortality and length of stay using machine learning
por: Iwase, Shinya, et al.
Publicado: (2022)

Predicting Mortality in Diabetic ICU Patients Using Machine Learning and Severity Indices
por: Anand, Rajsavi S., et al.
Publicado: (2018)

Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU
por: Kong, Guilan, et al.
Publicado: (2020)

Machine Learning Applications in the Neuro ICU: A Solution to Big Data Mayhem?
por: Chaudhry, Farhan, et al.
Publicado: (2020)

Predicting thromboembolic complications in COVID-19 ICU patients using machine learning
por: van de Sande, Davy, et al.
Publicado: (2020)

Early Prediction of Sepsis in the ICU Using Machine Learning: A Systematic Review
por: Moor, Michael, et al.
Publicado: (2021)

Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19
por: Subudhi, Sonu, et al.
Publicado: (2021)

Machine learning algorithms assist early evaluation of enteral nutrition in ICU patients
por: Wang, Ya-Xi, et al.
Publicado: (2023)

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU
por: Sikora, Andrea, et al.
Publicado: (2023)

Machine Learning for Early Prediction of Sepsis in Intensive Care Unit (ICU) Patients
por: Alanazi, Abdullah, et al.
Publicado: (2023)

Tracheostomy for Coronavirus Disease 2019 Patients: Maintaining the Standard of Care
por: Bassily-Marcus, Adel, et al.
Publicado: (2020)

Machine Learning for Medical Imaging
por: Fu, Geng-Shen, et al.
Publicado: (2019)

Deep Multi-Modal Transfer Learning for Augmented Patient Acuity Assessment in the Intelligent ICU
por: Shickel, Benjamin, et al.
Publicado: (2021)

E-CatBoost: An efficient machine learning framework for predicting ICU mortality using the eICU Collaborative Research Database
por: Safaei, Nima, et al.
Publicado: (2022)

Transferable Machine-Learning Model of the Electron Density
por: Grisafi, Andrea, et al.
Publicado: (2018)

Predicting ward transfer mortality with machine learning
por: Lezama, Jose L., et al.
Publicado: (2023)

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation
por: Vaid, Akhil, et al.
Publicado: (2020)

Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods
por: Burlina, Philippe, et al.
Publicado: (2017)

Readiness for transfer: a mixed-methods study on ICU transfers of care
por: Lee, Soo-Hoon, et al.
Publicado: (2023)

Benchmarking machine learning models on multi-centre eICU critical care dataset
por: Sheikhalishahi, Seyedmostafa, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_85ovs1oo75p2c0vdk9d4l92mdn