Abstract:
Disclosed are methods and systems for classifying one or more human subjects in one or more categories indicative of a health condition of the one or more human subjects. The method includes categorizing one or more parameters of each of the one or more human subjects in one or more data views based on a data type of each of the one or more parameters. A data view corresponds to a first data structure storing a set of parameters categorized in the data view, associated with each of the one or more human subjects. The one or more data views are transformed to a second data structure representative of the set of parameters across the one or more data views. Thereafter, a classifier is trained based on the second data structure, wherein the classifier classifies the one or more human subjects in the one or more categories.
Abstract:
Disclosed are the methods and systems for classifying one or more patients in one or more categories. A distribution of one or more physiological parameters associated with the one or more patients is determined based on a patient dataset. The one or more physiological parameters correspond to at least a stroke scale score. One or more parameters associated with a copula are estimated by the one or more processors. In an embodiment, the copula defines a joint distribution of the one or more physiological parameters. A classifier is created based on the one or more parameters, wherein the classifier classifies the one or more patients in the one or more categories. The one or more categories correspond to a range of the stroke scale score.