Why the study?
Can an automated machine-learning algorithm incorporating Poincaré analysis accurately quantify the severity of opioid-induced ataxic breathing?
Can an automated machine-learning algorithm incorporating Poincaré analysis accurately quantify the severity of opioid-induced ataxic breathing?
A machine-learning algorithm incorporating Poincaré analysis can feasibly quantify opioid-induced ataxic breathing severity, potentially aiding in the identification of opioid-induced respiratory depression.
May aid automated detection of opioid-induced respiratory depression; hypothesis-generating and requires prospective validation before clinical adoption.
We concluded it may be feasible for a machine-learning algorithm to quantify ataxic breathing severity in a manner consistent with a panel of domain experts. This methodology may be helpful in conjunction with traditional measures to identify patients experiencing OIRD.
No takes yet. Share an insight, caveat, or question.
Ermer et al. (2020) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: