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:
The disclosed embodiments illustrate methods and systems for assigning one or more tasks to a labor channel from one or more labor channels. The method includes selecting a first labor channel from said one or more labor channels based at least on a distribution of a performance metric associated with each of said one or more labor channels. The first labor channel is selected for execution of said one or more tasks. The method includes updating said distribution of said performance metric associated with each of said one or more labor channels. The method further includes selecting a second labor channel from said one or more labor channels based at least on a comparison between said updated distribution of said performance metric associated with said first labor channel, and said updated distribution of said performance metric associated with remaining one or more labor channels.