1. A method for providing personalized health support comprising: conducting biochemical assays at scheduled intervals on blood samples taken from an individual to provide, for each of a plurality of biochemical parameters, a time series of values representing the individual; extracting a plurality of clinical parameters associated with the individual from a knowledge base; determining a plurality of genomic parameters for the individual; calculating an expected time series for each of a plural subset of the plurality of biochemical parameters from at least the clinical parameters and the genomic parameters; comparing, for each of the plural subset of biochemical parameters, the time series of values representing the individual to the calculated expected time series to determine a likelihood of each of a plurality of conditions for the individual; wherein comparing the time series of values representing the individual to the calculated expected time series to determine the likelihood of each of the plurality of conditions for the individual comprises: determining a deviation of the time series of values from the calculated expected time series; applying the deviation as an input to a predictive model associated with one of the plurality of conditions, the predictive model being configured to determine the likelihood of the associated one of the plurality of conditions from at least one parameter derived from the deviation; outputting the likelihood of at least one of the plurality of conditions whereby a healthcare course of action can be made; storing each of the time series of values, the plurality of genomic parameters, and measured clinical outcomes in the knowledge base such that the knowledge base contains biochemical assays, genomic parameters, clinical parameters, and measured clinical outcomes for a population of patients; applying a data mining algorithm to the knowledge base to identify at least one causality case relating one of the clinical parameters, the genomic parameters, and the cohort parameters to a condition; and refining a predictive model according to the identified causality case.