Machine learning in anesthesiology: Detecting adverse events in clinical practice
The credibility of threshold-based alarms in anesthesia monitors is low and most of the warnings they produce are not informative. This study aims to show that Machine Learning techniques have a potential to generate meaningful alarms during general anesthesia without putting constraints on the type...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
NLM (Medline)
2022
|
| Subjects: | |
| Online Access: | View Fulltext in Publisher |