Cargando…
Semi-automated tracking of pain in critical care patients using artificial intelligence: a retrospective observational study
Monitoring the pain intensity in critically ill patients is crucial because intense pain can cause adverse events, including poor survival rates; however, continuous pain evaluation is difficult. Vital signs have traditionally been considered ineffective in pain assessment; nevertheless, the use of...
Autores principales: | Kobayashi, Naoya, Shiga, Takuya, Ikumi, Saori, Watanabe, Kazuki, Murakami, Hitoshi, Yamauchi, Masanori |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933166/ https://www.ncbi.nlm.nih.gov/pubmed/33664391 http://dx.doi.org/10.1038/s41598-021-84714-8 |
Ejemplares similares
-
Continuous visualization and validation of pain in critically ill patients using artificial intelligence: a retrospective observational study
por: Kobayashi, Naoya, et al.
Publicado: (2023) -
Semi-automated identification of biological control agent using artificial intelligence
por: Liao, Jhih-Rong, et al.
Publicado: (2020) -
Age-related changes in factors associated with delayed extubation after general anesthesia: a retrospective study
por: Kobayashi, Naoya, et al.
Publicado: (2020) -
Intensive care unit mortality and cost-effectiveness associated with intensivist staffing: a Japanese nationwide observational study
por: Ikumi, Saori, et al.
Publicado: (2023) -
Artificial intelligence–based technology for semi-automated segmentation of rectal cancer using high-resolution MRI
por: Hamabe, Atsushi, et al.
Publicado: (2022)