Abstract: Certain aspects of the present disclosure provide techniques for wound management and treatment. This includes determining characteristics of a wound for a patient based on an image of the wound, including detecting the characteristics based on analyzing the image using a first ML model. The techniques further include identifying patient medical data including characteristics relating to a medical history for the patient, and predicting a first care plan for the patient based on providing the characteristics of the wound and the patient medical data to a second ML model. The first care plan is configured to be used to treat the wound for the patient.

Abstract: Certain aspects of the present disclosure provide techniques for wound management and treatment. This includes determining characteristics of a wound for a patient based on an image of the wound, including detecting the characteristics based on analyzing the image using a first ML model trained to detect wound characteristics from a captured image. The techniques further include identifying patient medical data including characteristics relating to a medical history for the patient, and predicting a first care plan for the patient based on providing the characteristics of the wound and the patient medical data to a second ML model. The second ML model is trained to predict the first care plan using prior wound care outcome data including a prior wound care outcomes relating to prior patients. The first care plan is configured to be used to treat the wound for the patient.

Abstract: Certain aspects of the present disclosure provide a wound management system and method for predicting and avoiding wounds in a healthcare facility. The method includes collecting data relating to a patient’s health and applying a machine learning model to the data relating to the patient’s health to predict a first probability that the patient will sustain a first wound while the patient is at a first healthcare facility. The method also includes determining an action that reduces the first probability that the patient will sustain the first wound and communicating, to the first healthcare facility, a message indicating that the action should be taken to reduce the first probability that the patient will sustain the first wound while the patient is at the first healthcare facility.

Abstract: Certain aspects of the present disclosure provide a wound management system and method for predicting and treating wounds. The method includes collecting data relating to a patient's health and applying a machine learning model to the data relating to the patient's health to predict a first probability that the patient will sustain a first wound type outside of a care setting. The method also includes, in response to determining that the first probability exceeds a threshold, determining an action that reduces the first probability and communicating, to the patient, a message indicating the action should be taken to reduce the first probability that the patient will sustain the first wound type.

Abstract: Certain aspects of the present disclosure provide techniques for wound management and treatment. This includes determining characteristics of a wound for a patient based on an image of the wound, including detecting the characteristics based on analyzing the image using a first ML model. The techniques further include identifying patient medical data including characteristics relating to a medical history for the patient, and predicting a first care plan for the patient based on providing the characteristics of the wound and the patient medical data to a second ML model. The first care plan is configured to be used to treat the wound for the patient.

Abstract: Certain aspects of the present disclosure provide techniques for wound management and treatment. This includes determining characteristics of a wound for a patient based on an image of the wound, including detecting the characteristics based on analyzing the image using a first ML model trained to detect wound characteristics from a captured image. The techniques further include identifying patient medical data including characteristics relating to a medical history for the patient, and predicting a first care plan for the patient based on providing the characteristics of the wound and the patient medical data to a second ML model. The second ML model is trained to predict the first care plan using prior wound care outcome data including a prior wound care outcomes relating to prior patients. The first care plan is configured to be used to treat the wound for the patient.

Abstract: Certain aspects of the present disclosure provide techniques for predicting wound management treatment resources. This includes determining characteristics of a wound for a patient based on an image of the wound, including detecting the characteristics based on analyzing the image using a first machine learning (ML) model trained to detect wound characteristics from a captured image. The techniques further include predicting at least one of: (i) treatment resources or (ii) a treatment facility for treating the wound, including providing to a second trained ML model characteristics of the wound, patient medical data for the patient, and treatment facility data describing a plurality of available treatment facilities.

Abstract: Certain aspects of the present disclosure provide techniques for wound management and treatment. This includes determining characteristics of a wound for a patient based on an image of the wound, including detecting the characteristics based on analyzing the image using a first ML model trained to detect wound characteristics from a captured image. The techniques further include identifying patient medical data including characteristics relating to a medical history for the patient, and predicting a first care plan for the patient based on providing the characteristics of the wound and the patient medical data to a second ML model. The second ML model is trained to predict the first care plan using prior wound care outcome data including a prior wound care outcomes relating to prior patients. The first care plan is configured to be used to treat the wound for the patient.

Abstract: Various embodiments of the present invention provide an apparatus, method, and computer program product for mapping points of interest relative to a geometric shape defined on a map. More specifically, an apparatus, method, and computer program product is provided wherein a user may view on a map a geometric shape that depicts an area within a geographic region that is expected to be reachable from a point of interest within a threshold period of time.

Abstract: Various embodiments of the present invention provide an apparatus, method, and computer program product for mapping points of interest relative to a geometric shape defined on a map. More specifically, an apparatus, method, and computer program product is provided wherein a user may view on a map a geometric shape that depicts an area within a geographic region that is expected to be reachable from a point of interest within a threshold period of time.

Abstract: Touch sensor methods, devices and systems are disclosed. One embodiment of the present invention pertains to a touch sensing system comprising a touch screen having an array of multiple conductive nodes. A shape of each conductive node is designed such that a touch to a target conductive node generates a low capacitance on one or more neighboring conductive nodes of the target conductive node and a high capacitance generated on the target conductive node. The touch sensing system further may comprise a processor coupled to the touch screen for locating the touch by processing the low capacitance and the high capacitance, where the conductive nodes are coupled to their respective input/output (I/O) pins associated with the processor. Additionally, within the array, each target conductive node coupled to the same I/O pin may comprise a different neighboring conductive node.