Ontology highlight
ABSTRACT:
SUBMITTER: Lundberg SM
PROVIDER: S-EPMC6467492 | biostudies-literature | 2018 Oct
REPOSITORIES: biostudies-literature
Lundberg Scott M SM Nair Bala B Vavilala Monica S MS Horibe Mayumi M Eisses Michael J MJ Adams Trevor T Liston David E DE Low Daniel King-Wai DK Newman Shu-Fang SF Kim Jerry J Lee Su-In SI
Nature biomedical engineering 20181010 10
Although anaesthesiologists strive to avoid hypoxemia during surgery, reliably predicting future intraoperative hypoxemia is not currently possible. Here, we report the development and testing of a machine-learning-based system that, in real time during general anaesthesia, predicts the risk of hypoxemia and provides explanations of the risk factors. The system, which was trained on minute-by-minute data from the electronic medical records of over fifty thousand surgeries, improved the performan ...[more]