Pediatric anesthesia & critical care
From bytes to bedside: a systematic review on the use and readiness of artificial intelligence in the neonatal and pediatric intensive care unit
Authors' conclusion
The majority of AI models remain within the testing and prototyping phase and have a high risk of bias.
Study context
- Population
- Studies using artificial intelligence (AI) models during NICU or PICU staystudies included of 1257
- Participants
- 262 participants
- Outcome
- Maturity (technological readiness) of AI models in NICU and PICU treatment, their risk of bias and objectives
Methodological detailsSearched Medline ALL, Embase, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and Google Scholar
- Searched Medline ALL, Embase, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and Google Scholar
Pooled result
As reported in the abstract
Maturity, setting and risk of bias of AI models in NICU and PICU
Studies conducted in the NICU
66%
Studies with high risk of bias (main cause: insufficient sample size)
77%
Original publication
From bytes to bedside: a systematic review on the use and readiness of artificial intelligence in the neonatal and pediatric intensive care unit. Intensive Care Med. Published 12 September 2024. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →