Cargando…
Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services
BACKGROUND: In emergency medical services (EMSs), accurately predicting the severity of a patient’s medical condition is important for the early identification of those who are vulnerable and at high-risk. In this study, we developed and validated an artificial intelligence (AI) algorithm based on d...
Autores principales: | Kang, Da-Young, Cho, Kyung-Jae, Kwon, Oyeon, Kwon, Joon-myoung, Jeon, Ki-Hyun, Park, Hyunho, Lee, Yeha, Park, Jinsik, Oh, Byung-Hee |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057604/ https://www.ncbi.nlm.nih.gov/pubmed/32131867 http://dx.doi.org/10.1186/s13049-020-0713-4 |
Ejemplares similares
-
Artificial intelligence algorithm for predicting cardiac arrest using electrocardiography
por: Kwon, Joon-myoung, et al.
Publicado: (2020) -
Artificial intelligence algorithm for detecting myocardial infarction using six-lead electrocardiography
por: Cho, Younghoon, et al.
Publicado: (2020) -
Deep Learning–Based Algorithm for Detecting Aortic Stenosis Using Electrocardiography
por: Kwon, Joon‐Myoung, et al.
Publicado: (2020) -
Validation of deep-learning-based triage and acuity score using a large national dataset
por: Kwon, Joon-myoung, et al.
Publicado: (2018) -
Deep Learning in the Medical Domain: Predicting Cardiac Arrest Using Deep Learning
por: Lee, Youngnam, et al.
Publicado: (2018)