| abstract |
Machine-based risk prediction or assistance is provided for perioperative complications such as perioperative myocardial infarction (PMI). Machine learning models are used to predict the risk of PMI and/or recommend course of action to avoid PMI in PCI. In prediction, various combinations of types or modes of information are used, such as both imaging and non-imaging data. Machine learning models can be used to make predictions before, during, and/or after PCI to reduce the chance of PMI more quickly. Workflows for pre-PCI, during PCI, and/or post-PCI incorporate risk prediction and/or risk-based recommendations to reduce PMI in patients. |