Abstract: A method and system for communicating estimated blood loss parameters of a patient to a user, the method comprising: receiving data representative of an image, of a fluid receiver; automatically detecting a region within the image associated with a volume of fluid received at the fluid receiver, the volume of fluid including a blood component; calculating an estimated amount of the blood component present in the volume of fluid based upon a color parameter represented in the region, and determining a bias error associated with the estimated amount of the blood component; updating an analysis of an aggregate amount of the blood component and an aggregate bias error associated with blood loss of the patient, based upon the estimated amount of the blood component and the bias error; and providing information from the analysis of the aggregate amount of the blood component and the aggregate bias error, to the user.

Abstract: A machine causes capture of an image that depicts an optically readable code exhibited by a measurement device that corresponds to a scheduled medical procedure. The machine then determines, based on the optically readable code depicted by the captured image, a hardware identifier of a network interface of the measurement device and a location identifier of the measurement device. The machine next identifies the medical procedure based on the location identifier determined based on the optically readable code exhibited by the measurement device. The machine establishes a network connection with the measurement device based on the determined hardware identifier of the network interface of the measurement device. The established network connection may provide access to measurement data generated by the measurement device that corresponds to the scheduled medical procedure identified based on the location identifier of the measurement device.

Abstract: Systems and methods for assessing a flow of fluids suctioned from a patient. The flow of fluids may be divided according to a flow division ratio. An image of a first portion of the fluids may be evaluated to determine an estimated blood component quantity as a representative fraction of the flow of fluids. An intermittent estimate of blood loss may be determined based on the flow division ratio and the estimated blood component quantity, and a total estimate of blood loss updated based on the intermittent estimate. The representative fraction is projected or extended to be an estimated blood component quantity of the second portion of the fluids that bypasses the receptacle. The images may be continuously captured with a camera, and a fluid level of the fluids with a receptable may be continuously monitored. The total estimate of blood loss may be displayed in real-time on a display.

Abstract: Aspects of the disclosure relate to a machine-learning transaction-prediction engine for seasoning an anticipated manual transaction. The transaction may occur in a transaction session. The seasoning may occur prior to execution of the anticipated manual transaction. The transaction-prediction engine may include a receiving/storage module configured to receive and store identification information of the transactor. The engine may also include a step-retrieval module configured to retrieve a set of in-session transaction steps associated with the transactor. In addition, the engine may include a history-retrieval module configured to retrieve, based on the stored identification information, historical transactional information associated with the transactor. The historical transaction information comprising a plurality of historical transaction patterns associated with the transactor.

Abstract: Systems and methods for assessing fluids from a patient are disclosed. The system includes a receptacle including an inlet port, an outlet port, and a third port; a valve system in fluidic communication with the receptacle; and one or more features in the receptacle to aid in optical imaging of fluids. The system has a fill mode and a flush mode. In the fill mode, the valve system directs suction from a vacuum source through the third port into the receptacle, thereby drawing fluid through the inlet port into the receptacle. In the flush mode, the valve system directs suction from the vacuum source through the outlet port, thereby drawing fluid through the outlet port out of the receptacle. Fluid-related information such as, for example, concentration of a blood component, may be estimated based on images of fluids in the receptacle.

Abstract: Aspects of the disclosure relate to a machine-learning transaction-prediction engine for seasoning an anticipated manual transaction. The transaction may occur in a transaction session. The seasoning may occur prior to execution of the anticipated manual transaction, The transaction-prediction engine may include a receiving/storage module configured to receive and store identification information of the transactor. The engine may also include a step-retrieval module configured to retrieve a set of in-session transaction steps associated with the transactor. In addition, the engine may include a history-retrieval module configured to retrieve, based on the stored identification information, historical transactional information associated with the transactor. The historical transaction information comprising a plurality of historical transaction patterns associated with the transactor.

Abstract: Systems and methods for assessing fluids from a patient are disclosed. The system includes a receptacle including an inlet port, an outlet port, and a third port; a valve system in fluidic communication with the receptacle; and one or more features in the receptacle to aid in optical imaging of fluids. The system has a fill mode and a flush mode. In the fill mode, the valve system directs suction from a vacuum source through the third port into the receptacle, thereby drawing fluid through the inlet port into the receptacle. In the flush mode, the valve system directs suction from the vacuum source through the outlet port, thereby drawing fluid through the outlet port out of the receptacle. Fluid-related information such as, for example, concentration of a blood component, may be estimated based on images of fluids in the receptacle.

Abstract: One method for counting surgical samples comprises: identifying a physical sample in a field of view of an optical sensor; indexing a sample counter for the identified physical sample; extracting a feature from a portion of the field of the view of the optical sensor; and estimating the extracorporeal blood volume in a portion of the physical sample based upon the extracted feature.

Abstract: One method for counting surgical samples comprises: identifying a physical sample in a field of view of an optical sensor; indexing a sample counter for the identified physical sample; extracting a feature from a portion of the field of the view of the optical sensor; and estimating the extracorporeal blood volume in a portion of the physical sample based upon the extracted feature.