Abstract: Techniques for machine learning-based dropout severity prediction are provided. Usage information for a patient is accessed, the usage information indicating participation, by the patient, in a respiratory therapy. A dropout event with respect to the respiratory therapy is identified based on evaluating the usage information using a consolidated usage rule. In response to identifying the dropout event, a dropout severity prediction is generated based on the usage information and a trained machine learning model. In response to determining that the dropout severity prediction satisfies one or more criteria, one or more interventions for the patient are initiated.

Abstract: A method of optimizing a plurality of parameters of a respiratory therapy system comprises receiving user data associated with a user of the respiratory therapy system. The method further comprises determining an initial value of each of the plurality of parameters is based at least in part on the user data. Each of the plurality of parameters is associated with a comfort level of the user. The method further comprises receiving usage data associated with use of the respiratory therapy system during a first period of time in which each of the plurality of parameters has its initial value. The method further comprises generating a recommended value of each of the plurality of parameters for use of the respiratory therapy system during a second period of time after the first period of time, based at least in part on the user data and the usage data.

Abstract: Methods, systems, and devices are described for managing wake locks in a wireless communication device. The described methods, systems and devices may enable a wireless communication device to monitor activity of an application for which a wake lock is held. The described approach may manage the wake lock based at least in part on the activity or inactivity of the application. For example, when the application is inactive or has activity below a particular threshold for a certain amount of time, the described approach may determine to release the wake lock.

Abstract: Methods, systems, and devices are described for managing wake locks in a wireless communication device. The described methods, systems and devices may enable a wireless communication device to monitor activity of an application for which a wake lock is held. The described approach may manage the wake lock based at least in part on the activity or inactivity of the application. For example, when the application is inactive or has activity below a particular threshold for a certain amount of time, the described approach may determine to release the wake lock.