Abstract: A computer-implemented method and system for analyzing data related to a plurality of healthcare delivery units includes: collecting data from different data sources related to the plurality of healthcare delivery units; computing, based on the collected data, for individual patients associated with any one of the plurality of healthcare delivery units, an expected frequency of at least one type of health outcome for each of the individual patients; and generalizing the computed expected frequencies of the at least one type of health outcome for the individual patients into one or more individual-level impact metrics associated with one or more risk factors for the at least one type of health outcome. The one or more risk factors include one or more modifiable risk factors and one or more un-modifiable risk factors.

Abstract: The present disclosure relates to a method for calculating or estimating at least one medical value based on several input values using artificial intelligence.

Abstract: A computer-implemented method of generating a generalized model for adaptively predicting occurrence or progression of a first adverse health condition for a first subpopulation arbitrarily selected from a total population, includes extracting information about characterizing features of a plurality of second subpopulations, about occurrences and/or severity of the first adverse health condition found therein and/or about corresponding prognostic results, from a plurality of publications. One or more of the characterizing features are associated with corresponding first factors indicating a relation with an adverse or beneficial contribution of the characterizing feature to the occurrence or progression of the first adverse health condition, and with corresponding second factors indicating the relative frequency of occurrence in the respective second subpopulation considered in the respective publication.

Abstract: A system relating to medical treatment, such as hemodialysis or peritoneal dialysis, for determining user-centric treatment data includes a user device and a central device. The user device and the central device each include a wireless communication component. The wireless communication component of the central device and/or the wireless communication component of the user device is/are configured to distinguish between the user device being in a first location and the user device being in a second location, wherein the first location is associated with a treatment area and the second location is associated with a general purpose area. The user device and/or the central device is configured to determine, based on the user device being in the first location and/or the user device being in the second location, an overall treatment time and an overall spent time.

Abstract: The present disclosure relates to a method for calculating or estimating at least one medical value based on several input values using artificial intelligence.

Abstract: A system relating to medical treatment, such as hemodialysis or peritoneal dialysis, for determining user-centric treatment data includes a user device and a central device. The user device and the central device each include a wireless communication component. The wireless communication component of the central device and/or the wireless communication component of the user device is/are configured to distinguish between the user device being in a first location and the user device being in a second location, wherein the first location is associated with a treatment area and the second location is associated with a general purpose area. The user device and/or the central device is configured to determine, based on the user device being in the first location and/or the user device being in the second location, an overall treatment time and an overall spent time.