Cargando…
Prediction of In-Hospital Cardiac Arrest Using Shallow and Deep Learning
Sudden cardiac arrest can leave serious brain damage or lead to death, so it is very important to predict before a cardiac arrest occurs. However, early warning score systems including the National Early Warning Score, are associated with low sensitivity and false positives. We applied shallow and d...
Autores principales: | Chae, Minsu, Han, Sangwook, Gil, Hyowook, Cho, Namjun, Lee, Hwamin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8307337/ https://www.ncbi.nlm.nih.gov/pubmed/34359337 http://dx.doi.org/10.3390/diagnostics11071255 |
Ejemplares similares
-
Deep Learning in the Medical Domain: Predicting Cardiac Arrest Using Deep Learning
por: Lee, Youngnam, et al.
Publicado: (2018) -
An Algorithm Based on Deep Learning for Predicting In‐Hospital Cardiac Arrest
por: Kwon, Joon‐myoung, et al.
Publicado: (2018) -
Efficient shallow learning as an alternative to deep learning
por: Meir, Yuval, et al.
Publicado: (2023) -
Prospective, multicenter validation of the deep learning-based cardiac arrest risk management system for predicting in-hospital cardiac arrest or unplanned intensive care unit transfer in patients admitted to general wards
por: Cho, Kyung-Jae, et al.
Publicado: (2023) -
Evaluation of deep and shallow learning methods in chemogenomics for the prediction of drugs specificity
por: Playe, Benoit, et al.
Publicado: (2020)