System and Method for Dynamically Adaptable Learning Medical Diagnosis System
First Claim
1. A system for determining a likelihood of a disease:
- a patient history database containing records each having a plurality of data fields related to a particular patient;
an analyzing network having access to the patient history database and having a plurality of features based on the plurality of data fields included in the records to analyze the plurality of data fields to determine a likelihood of the disease based on the plurality of features; and
a learning network having access to the analyzing network to review the likelihood of the disease determined by the analyzing network and the plurality of data fields included in the records and automatically identify, evaluate, and add new features to the analyzing network that at least improve determinations of a likelihood of the disease.
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Accused Products
Abstract
A system and method for determining a likelihood of a disease presence in a particular patient includes a patient history database containing records. Each record includes a plurality of data fields related to a particular patient. An analyzing network is provided having access to the patient history database and having features based on the plurality of data fields included in the records to analyze the plurality of data fields and determine a likelihood of disease presence based on the plurality of features. A learning network is provided that has access to the analyzing network to review the likelihood of disease presence determined by the analyzing network and the plurality of data fields included in the records and automatically identify, evaluate, and add new features to the analyzing network that improve determinations of a likelihood of the disease.
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Citations
20 Claims
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1. A system for determining a likelihood of a disease:
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a patient history database containing records each having a plurality of data fields related to a particular patient; an analyzing network having access to the patient history database and having a plurality of features based on the plurality of data fields included in the records to analyze the plurality of data fields to determine a likelihood of the disease based on the plurality of features; and a learning network having access to the analyzing network to review the likelihood of the disease determined by the analyzing network and the plurality of data fields included in the records and automatically identify, evaluate, and add new features to the analyzing network that at least improve determinations of a likelihood of the disease. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method for developing a system for determining a likelihood of a disease:
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providing a database of patient records; building a Bayesian network to access the database of patient records, analyze a particular patient record in the database, and provide a likelihood of the disease in a patient corresponding to the particular patient record; and automatically augmenting the Bayesian network using a learning network having access to the Bayesian network to review the likelihood of the disease determined by the analyzing network and the patient records, wherein the augmentation includes adding new features to the Bayesian network that improve determinations of a likelihood of the disease. - View Dependent Claims (12, 13, 14)
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15. A system for determining a disease state:
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a patient history database containing records each having a plurality of data fields related to a particular patient; a Bayesian network having access to the patient history database and having a plurality of features based on the plurality of data fields included in the records to analyze the plurality of data fields and determine a disease state of a particular patient; and a learning network having access to the Bayesian network to review the determined disease state and the plurality of data fields included in the records and automatically identify and evaluate potential new features that, if added to the Bayesian network, would improve determinations of the disease state. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification