Читать книгу Machine Learning for Healthcare Applications - Группа авторов - Страница 44

Let At be the set of daily life activities done by an individual t day’s back. Thus, A0 is the set of activities done by an individual today, A1 be the set of activities done by an individual yesterday, and so on. A is the collection of the activities of an individual for many days. M be the set of physical measures of an individual. H be the health status matrix.

Definition 1: Health Status Matrix: A health status matrix M describes the outcome of various parameters of health status. Each row of the matrix is considered as a vector of possible outcomes of the respective parameter of the health status. Examples of health status parameters are sleep status, smoke status, drink status, etc.

Given a set of daily life activities and physical measures of users over a few days and their health status. The health status of a set of users already defined, known as labeled users UL. Whereas the health status of other sets of users is not defined, known as unlabeled users U_V. The aim of the proposed model is to learn a function that uses the information of the labeled users’ UL and find the health status of the unlabeled users U_V.

Given a series of activities from last t days, the objective is to learn a function F,

where M is the set of physical measures of a user At is the set of activities of the user t days back. H is a health status matrix