Cargando…
A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study
BACKGROUND: The treatment and care of adults and children with traumatic brain injury (TBI) constitute an intractable global health problem. Predicting the prognosis and length of hospital stay of patients with TBI may improve therapeutic effects and significantly reduce societal health care burden....
Autores principales: | Fang, Cheng, Pan, Yifeng, Zhao, Luotong, Niu, Zhaoyi, Guo, Qingguo, Zhao, Bing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9789495/ https://www.ncbi.nlm.nih.gov/pubmed/36485032 http://dx.doi.org/10.2196/41819 |
Ejemplares similares
-
Construction of a predictive model based on MIV-SVR for prognosis and length of stay in patients with traumatic brain injury: Retrospective cohort study
por: Pan, Yifeng, et al.
Publicado: (2023) -
Effect of intensive glycaemic control on moderate hypoglycaemia and ICU length of stay in severe traumatic brain injury
por: Núñez-Patiño, Rafael A., et al.
Publicado: (2018) -
Effect of an early occupational therapy intervention on length of stay in moderate and severe traumatic brain injury patients
por: Alkhawaldeh, Omar Ibrahim, et al.
Publicado: (2022) -
Effect of rehabilitation length of stay on outcomes in individuals with traumatic brain injury or spinal cord injury: a systematic review protocol
por: Lamontagne, Marie-Eve, et al.
Publicado: (2013) -
Correlation between intracranial pressure monitoring for severe traumatic brain injury with hospital length of stay and discharge disposition: a retrospective observational cohort study
por: Foote, Christopher W., et al.
Publicado: (2022)