Patents by Inventor Rudolph John Freese

Rudolph John Freese has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20170032088
    Abstract: This invention uses non-parametric statistical measures and probability mathematical techniques to calculate deviations of variable values, on both the high and low side of a data distribution, from the midpoint of the data distribution. It transforms the data values and then combines all of the individual variable values into a single scalar value that is a “good-ness” score. This “good-ness” behavior score model characterizes “normal” or typical behavior, rather than predicting fraudulent, abusive, or “bad”, behavior. The “good” score is a measure of how likely it is that the subject's behavior characteristics are from a population representing a “good” or “normal” provider, claim, beneficiary or healthcare merchant behavior. The “good” score can replace or compliment a score model that predicts “bad” behavior in order to reduce false positive rates. The optimal risk management prevention program should include both a “good” behavior score model and a “bad” behavior score model.
    Type: Application
    Filed: October 11, 2016
    Publication date: February 2, 2017
    Applicant: Risk Management Solutions LLC
    Inventors: Allen Jost, Rudolph John Freese, Walter Allan Klindworth
  • Publication number: 20130085769
    Abstract: This invention uses non-parametric statistical measures and probability mathematical techniques to calculate deviations of variable values, on both the high and low side of a data distribution, from the midpoint of the data distribution. It transforms the data values and then combines all of the individual variable values into a single scalar value that is a “good-ness” score. This “good-ness” behavior score model characterizes “normal” or typical behavior, rather than predicting fraudulent, abusive, or “bad”, behavior. The “good” score is a measure of how likely it is that the subject's behavior characteristics are from a population representing a “good” or “normal” provider, claim, beneficiary or healthcare merchant behavior. The “good” score can replace or compliment a score model that predicts “bad” behavior in order to reduce false positive rates. The optimal risk management prevention program should include both a “good” behavior score model and a “bad” behavior score model.
    Type: Application
    Filed: September 14, 2012
    Publication date: April 4, 2013
    Applicant: RISK MANAGEMENT SOLUTIONS LLC
    Inventors: Allen Jost, Rudolph John Freese, Walter Allan Klindworth