As with any computerized algorithmic analysis, the amount of raw data entered into the algorithm determines the sensitivity of the output. The more raw data you enter into the system the more precise and certain the output. We do build in a degree of uncertainty into our system whereby the absence of important biomarkers plays a role in the probability that a certain system is out of balance or a clinical condition is likely. For instance, the sensitivity of Endothelial Dysfunction requires a number of biomarkers to be present in the sample to give a representation of the probability that endothelial dysfunction is present. If you only have 1 or 2 biomarkers and none of the others then the degree of uncertainty goes up and the probability score goes down. The short answer is please use as many biomarkers as possible in order to give the algorithms enough data to report the probability findings.