| 摘要 |
Disclosed are embodiments of methods and systems for predicting a health condition of a first human subject. The method comprises extracting a historical data including physiological parameters of one or more second human subjects. A latent variable is determined based on an inverse cumulative distribution of a transformed historical data, determined by ranking of the historical data. Further, one or more parameters of a first distribution, deterministic of health conditions in the historical data, are determined based on the latent variable. For each physiological parameter, a random variable is sampled from a second distribution of the physiological parameter based on the one or more parameters. Further, based on the random variable, the latent variable is updated. Thereafter, the one or more parameters are re-estimated based on the updated latent variable. Based on the first distribution a classifier is trained to predict the health condition of the first human subject. |
| 主权项 |
1. A method for predicting a health condition of a first human subject, the method comprising:
extracting, by one or more processors, a historical data comprising a measure of one or more physiological parameters associated with each of one or more second human subjects; determining, by said one or more processors, a latent variable based on an inverse cumulative distribution of a transformed historical data, wherein said transformed historical data is determined by ranking of said historical data; estimating, by said one or more processors, one or more parameters of a first distribution deterministic of one or more health conditions in said historical data, based on said latent variable; for each physiological parameter from said one or more physiological parameters: sampling, by said one or more processors, a random variable from a second distribution of said physiological parameter, based on said one or more parameters; updating, by said one or more processors, said latent variable based on said random variable; re-estimating, by said one or more processors, said one or more parameters based on said updated latent variable; training, by said one or more processors, a classifier based on said first distribution; receiving, by said one or more processors, a measure of said one or more physiological parameters associated with said first human subject; and predicting, by said one or more processors, said health condition of said first human subject by utilizing said classifier based on said received measure of said one or more physiological parameters associated with said first human subject. |
