Abstract: Methods and systems for predicting whether a patient is likely to develop post-cardiotomy cardiogenic shock (PCCS) are described. The method includes receiving medical information for a patient, extracting one or more features from the received medical information, providing the one or more features as input to a trained classification model configured to output a risk assessment that the patient is likely to develop PCCS, and outputting an indication of the risk assessment.

Abstract: A system for monitoring surgical objects is provided. An entry scanner captures a first set of image data from a surgical object identifier. A containment surface defines a target field of view. An exit scanner captures a second set of image data from a surgical object identifier within the target field of view. A monitoring system is electrically connected to at least one of the entry and exit scanners. The monitoring system has a surgical object recognition module having a database of pre-existing surgical object identifier data. The surgical recognition module identifies at least one of the number of surgical objects, the type of surgical objects, and the number of each type of surgical objects from the first and second sets of image data by comparing the first and second sets of image data with the pre-existing surgical object identifier data.

Abstract: The present disclosure relates to a system and method for recognizing objects used in a medical procedure using a convolutional neural network. No database of image information for such objects is used or required. Rather, the neural network is trained to recognize the objects, and does not require any such image database. The system is able to reconcile the recognized objects against a ‘counted-in’ list of objects for the procedure, to ensure that all such objects are accounted for prior to closing the procedure.

Abstract: A system for monitoring surgical objects is provided. An entry scanner captures a first set of image data from a surgical object identifier. A containment surface defines a target field of view. An exit scanner captures a second set of image data from a surgical object identifier within the target field of view. A monitoring system is electrically connected to at least one of the entry and exit scanners. The monitoring system has a surgical object recognition module having a database of pre-existing surgical object identifier data. The surgical recognition module identifies at least one of the number of surgical objects, the type of surgical objects, and the number of each type of surgical objects from the first and second sets of image data by comparing the first and second sets of image data with the pre-existing surgical object identifier data.