Back to results
US 2022/0015834 A1Published application
System and method for selecting and implementing a bariatric surgery
AssigneeSmart N.V.
InventorGus J. SLOTMAN
Life of this patent
Estimating the term…
Abstract
This invention relates to a method and network system for selecting an appropriate bariatric surgery for a patient based upon baseline patient parameters.
Claims5
A computer-implemented method for selecting and implementing a patient-specific bariatric surgery, the method comprising:
- receiving a baseline data set of a patient, the baseline data set including at least age, comorbidities, and employment for the patient;
- comparing the patient data set to a plurality of reference patient data sets to identify similar patient data sets in the plurality of reference patient data sets, wherein said comparison comprises linear regression modeling of independent variables for weight and weight loss as dependent variables, and logistic regression modeling of independent variables for comorbidities as dependent variables, wherein the independent variables comprise at least one of age or employment and wherein the reference patient data sets comprise patients receiving treatments with a plurality of bariatric surgeries;
- identifying similar patient data sets from the reference patient data sets comprising a target treatment outcome associated with the plurality of bariatric surgeries;
- calculating, for each of the plurality of bariatric surgeries, a probability of achieving the target treatment outcome for the patient;
- selecting and implementing at least one of the plurality of bariatric surgeries for the patient, based on the calculated probability of achieving the target treatment outcome.
2 more elements
A system for selecting and implementing a patient-specific bariatric surgery for a patient, the system comprising:
- one or more processors;
- and
- a memory storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising:
- receiving a baseline data set of a patient, the baseline data set including at least age, comorbidities, and employment for the patient;
- comparing the patient data set to a plurality of reference patient data sets to identify similar patient data sets in the plurality of reference patient data sets, wherein said comparison comprises linear regression modeling of independent variables for weight and weight loss as dependent variables, and logistic regression modeling of independent variables for comorbidities as dependent variables, wherein the independent variables comprise at least one of age or employment and wherein the reference patient data sets comprise patients receiving treatments with a plurality of bariatric surgeries;
- identifying similar patient data sets from the reference patient data sets comprising a target treatment outcome associated with the plurality of bariatric surgeries;
- calculating, for each of the plurality of bariatric surgeries, a probability of achieving the target treatment outcome for the patient;
- and
- selecting at least one of the plurality of bariatric surgeries for the patient, based on the calculated probability of achieving the target treatment outcome.
6 more elements
Dependencies are inferred from the claim text.