Method for screening and treating patients at risk of medical disorders
First Claim
1. A method for predicting weight loss outcome of application of a proposed therapy to a patient for treating an eating, gastrointestinal, or gastroesophageal disorder, comprising:
- a) obtaining items of information from the patient at risk of the eating, gastrointestinal, or gastroesophageal disorder, each item of information relating to a preselected patient variable; and
b) predicting the weight loss outcome for the patient from the obtained items of information for the patient using an aggregated weight loss predictor developed from i) observed similar types of information and corresponding weight loss information obtained from an actual population of patients who previously received a similar therapy to the proposed therapy for the patient, or ii) information generated from a simulated population of patients by resampling the observed actual population information to produce pseudo-replicates;
wherein predicting the weight loss outcome comprises processing the items of information using an aggregated classification and repression tree model formed using a committee or ensemble method combining multiple predictors trained in perturbed versions of the observed similar types of information and corresponding weight loss information obtained from the actual population of patients.
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Abstract
Method for screening patients to predict which patients at risk of a medical disorder, such as morbid obesity, gastrointestinal problems, or gastroesophageal problems, will be responders, and conversely, which patients will not, to achieve a favorable outcome from therapy for that disorder. This method supports an intervention strategy for patients having weight or gastrointestinal problems that will cut health costs. It enables patients and care-givers alike to more efficiently use their time, efforts and resources by enabling an early selection of an appropriate treatment modality for a given patient. Its application also extends to other implantable medical devices and therapies using them.
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Citations
43 Claims
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1. A method for predicting weight loss outcome of application of a proposed therapy to a patient for treating an eating, gastrointestinal, or gastroesophageal disorder, comprising:
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a) obtaining items of information from the patient at risk of the eating, gastrointestinal, or gastroesophageal disorder, each item of information relating to a preselected patient variable; and b) predicting the weight loss outcome for the patient from the obtained items of information for the patient using an aggregated weight loss predictor developed from i) observed similar types of information and corresponding weight loss information obtained from an actual population of patients who previously received a similar therapy to the proposed therapy for the patient, or ii) information generated from a simulated population of patients by resampling the observed actual population information to produce pseudo-replicates; wherein predicting the weight loss outcome comprises processing the items of information using an aggregated classification and repression tree model formed using a committee or ensemble method combining multiple predictors trained in perturbed versions of the observed similar types of information and corresponding weight loss information obtained from the actual population of patients. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26)
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27. A method of screening or optimization of a prospective patient in advance of a medical treatment, comprising:
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a) developing a predictive model for outcomes of patients who will receive the medical treatment as part of a therapy or treatment of a medical condition or disorder, using data mining techniques, and advanced regression tree analysis to build, train and test the predictive model for predicting the outcomes of patients receiving the medical treatment; b) collecting data from the prospective patient for the medical treatment; c) using the predictive model to predict the possible outcome of the prospective patient for the medical treatment. - View Dependent Claims (28, 29, 30, 31, 32)
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33. A method of screening or optimization of a prospective patient in advance of the application of an obesity therapy, comprising:
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a) developing a predictive model for outcomes of patients who will have the obesity therapy as part of a treatment for obesity and comorbidities thereof, using data mining techniques, and advanced regression tree analysis to build, train and test the predictive model for predicting the outcomes of patients receiving the obesity therapy; b) collecting data from the prospective patient for the obesity therapy; c) using the predictive model to predict the possible outcome of the prospective patient for the obesity therapy. - View Dependent Claims (34, 35, 36, 37, 38, 39, 40, 41, 42, 43)
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Specification