Abstract: Systems and methods for treating a subject are provided. A first dataset comprising timestamped autonomous glucose measurements of the subject over a first time course is obtained. A second dataset, associated with a standing insulin regimen for the subject over the first time course and comprising insulin medicament records, is also obtained. Each record comprises a timestamped injection event including an amount and type of insulin medicament injected into the subject by an insulin pen. The first and second datasets serve to calculate a glycaemic risk measure and an insulin sensitivity factor of the subject during the first time course, which are used to obtain a basal titration schedule and a fasting blood glucose profile model over a subsequent second time course for the subject. The model predicts the fasting blood glucose level of the subject based upon amounts of basal insulin medicament injected into the subject.

Abstract: Systems and methods are described for automatically identifying fraud, waste or abuse in health insurance claims submitted to insurance companies by healthcare providers. Insurance claim information and at one image associated with the insurance claim may be received, where the image has been submitted by a healthcare provider to an insurance carrier as supporting evidence of a medical service performed by the healthcare provider. The system may generate a digital signature representing the image, then may compare the digital signature generated for the image to previously generated digital signatures of other images that have been submitted in association with other insurance claims. The system may then determine a likelihood that the given insurance claim is associated with fraud, waste or abuse, based in part on whether the digital signature is identical or close to one or more of the previously generated digital signatures.