Predisposition prediction using attribute combinations
First Claim
1. A computer based method for predisposition prediction wherein a relative likelihood of medical disease predisposition for an individual may be determined based on datasets containing predetermined association of attributes combining pangenetic and non-pangenetic attributes and combinations thereof with said disease, said method performed on a computer including a user interface, a processor, a memory, and a display, comprising:
- a) said computer receiving a medical disease associated query attribute via said user interface into said processor;
b) said processor accessing an attribute profile of said individual contained in said memory;
c) said processor accessing a stored dataset in said memory containing said predetermined attribute combinations combining pangenetic and non-pangenetic attributes and statistical results that indicate the strength of association of each of the attribute combinations in said stored dataset, said statistical association having been created by comparing previously submitted and assessed attribute profiles of individuals with the medical disease query attribute and comparing the submitted attribute profiles with attributes profiles of those not having the medical disease query, so as to minimize the impact of shared attribute combinations;
d) identifying attribute combinations from the stored dataset of predetermined attribute combinations associated with said medical disease that occur in the attribute profile of said individual by comparing the attribute combinations occurring in both the attribute profile of the individual and in the dataset attribute profiles; and
e) generating a dataset ranked output of one or more predisposition predictions for the individual based on the identified attribute combinations appearing in both the predetermined dataset and in the attribute profile of said individual and the statistical results indicating a relative predisposition of said individual to acquire said disease.
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0 Petitions
Accused Products
Abstract
A method and system are presented in which predisposition predictions are generated for an individual with respect to an attribute indicated in a query. The predictions are based on the identification of predisposing attribute combinations within the attribute profile of the individual and statistical results that indicate the strength of association of the identified attribute combinations with the query attribute.
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Citations
21 Claims
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1. A computer based method for predisposition prediction wherein a relative likelihood of medical disease predisposition for an individual may be determined based on datasets containing predetermined association of attributes combining pangenetic and non-pangenetic attributes and combinations thereof with said disease, said method performed on a computer including a user interface, a processor, a memory, and a display, comprising:
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a) said computer receiving a medical disease associated query attribute via said user interface into said processor; b) said processor accessing an attribute profile of said individual contained in said memory; c) said processor accessing a stored dataset in said memory containing said predetermined attribute combinations combining pangenetic and non-pangenetic attributes and statistical results that indicate the strength of association of each of the attribute combinations in said stored dataset, said statistical association having been created by comparing previously submitted and assessed attribute profiles of individuals with the medical disease query attribute and comparing the submitted attribute profiles with attributes profiles of those not having the medical disease query, so as to minimize the impact of shared attribute combinations; d) identifying attribute combinations from the stored dataset of predetermined attribute combinations associated with said medical disease that occur in the attribute profile of said individual by comparing the attribute combinations occurring in both the attribute profile of the individual and in the dataset attribute profiles; and e) generating a dataset ranked output of one or more predisposition predictions for the individual based on the identified attribute combinations appearing in both the predetermined dataset and in the attribute profile of said individual and the statistical results indicating a relative predisposition of said individual to acquire said disease. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A computer based system for predisposition prediction wherein a relative likelihood of medical disease predisposition for an individual may be determined based on datasets containing predetermined association of attributes combining pangenetic and non-pangenetic attributes and combinations thereof with said disease, comprising:
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a) a data receiving subsystem processor for receiving a query attribute associated with said medical disease; b) a first data accessing subsystem memory for accessing a previously stored attribute profile of said individual; c) a second data accessing subsystem memory for accessing a dataset containing previously stored attribute combinations combining pangenetic and non-pangenetic attributes and statistical results that indicate the strength of association of each of the attribute combinations in said stored dataset with the medical disease query attribute, said statistical strength of association having been created by comparing previously submitted and assessed attribute profiles of individuals with the medical disease query attribute and comparing the submitted attribute profiles with attributes profiles of those not having the medical disease query, so as to minimize the impact of shared attribute combinations; d) a data processing subsystem processor comprising; i) a data comparison subsystem means for identifying attribute combinations from the stored data set that occur in the attribute profile of said individual; and ii) a statistical predisposition prediction subsystem means for generating and displaying one or more predisposition predictions for the individual based on the identified attribute combinations and the statistical results indicating a relative predisposition of said individual to acquire said disease, said prediction of relative predisposition obtained by comparing the attribute combinations occurring in both the attribute profile of the individual and in the respective dataset of attribute profiles. - View Dependent Claims (17, 18, 19, 20)
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21. A computer based system for predisposition prediction wherein a relative likelihood of medical disease predisposition for an individual may be determined based on datasets containing predetermined association of attributes combining pangenetic and non-pangenetic attributes and combinations thereof with the disease, the computer based system comprising:
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a) a data receiving subsystem for receiving a query attribute associated with said medical disease; b) a first data accessing subsystem for accessing a first computer memory containing a previously stored attribute profile of the individual; c) a second data accessing subsystem for accessing a second computer memory containing a dataset having previously stored attribute combinations combining pangenetic and non-pangenetic attributes and statistical results that indicate the strength of association of each of the attribute combinations in said stored dataset with the medical disease query attribute, said statistical strength of association having been created by comparing previously submitted and assessed attribute profiles of individuals with the medical disease query attribute and comparing the submitted attribute profiles with attributes profiles of those not having the medical disease query, so as to eliminate the impact of shared attribute combinations; d) a data processor and an associated memory, wherein the associated memory contains machine readable instructions which upon execution by the data processor, execute the method of; i) identifying attribute combinations from the stored data set that occur in the attribute profile of said individual; and ii) generating and transmitting for display one or more predisposition predictions for the individual based on the identified attribute combinations and the statistical results indicating a relative predisposition of said individual to acquire the disease, the prediction of relative predisposition obtained by comparing the attribute combinations occurring in both the attribute profile of the individual and in the respective dataset of attribute profiles.
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Specification