Abstract: An unsupervised statistical analytics approach to detecting fraud utilizes cluster analysis to identify specific clusters of claims or transactions for additional investigation, or utilizes association rules as tripwires to identify outliers. The clusters or sets of rules define a “normal” profile for the claims or transactions used to filter out normal claims, leaving “not normal” claims for potential investigation. To generate clusters or association rules, data relating to a sample set of claims or transactions may be obtained, and a set of variables used to discover patterns in the data that indicate a normal profile. New claims may be filtered, and not normal claims analyzed further. Alternatively, patterns for both a normal profile and an anomalous profile may be discovered, and a new claim filtered by the normal filter. If the claim is “not normal” it may be further filtered to detect potential fraud.

Abstract: Methods of forming proteinaceous products such as cell culture supplement capable of supporting the growth and culturing of cells, tissue, and organs, are generally disclosed. One method generally provides for the collection of the internal tissue of an animal, such as a bovine, and the processing of the internal tissue to degrade and/or lyse the tissue components. A cell culture supplement or other proteinaceous product can be prepared from the processed tissue. A proteinaceous product can include, for example, a complete protein profile of the tissue or only certain biological factors extracted from the tissue. Collected internal tissue can be lymphatic tissue such as the supramammary glands of a dairy or beef cow or the thymus gland of a veal calf.