Computer architecture and process of patient generation, evolution, and simulation for computer based testing system using bayesian networks as a scripting language
First Claim
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1. A method for educating or evaluating a user, comprising the steps of:
- instantiating a virtual patient for display to the user, the virtual patient including a plurality of health states;
receiving from the user at least one of a query for a medical finding concerning the instantiated virtual patient and a course of action; and
at least one one of;
generating, responsive to the received query, a specific medical finding at least in part from a first network defining a health state reveal structure corresponding to the instantiated virtual patient;
generating, responsive to the received query, an indication of an inappropriate query, based, at least in part, on a second network defining a medical practice management plan; and
generating, responsive to the received course of action, an indication of an inappropriate course of action, based, at least in part, on the second network.
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Abstract
A method and system for patient generation and evolution for a computer-based testing system and/or expert system. One or more belief networks, which describe parallel health state networks are accessed by a user or a computer. A knowledge base, at least in part, is scripted from the one or more belief networks by the computer. A model patient at least in part, is instantiated by the computer from the scripted knowledge base. Optionally, the model patient is evolved by the computer in accordance with the parallel health state networks and responsive to a received course of action.
91 Citations
21 Claims
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1. A method for educating or evaluating a user, comprising the steps of:
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instantiating a virtual patient for display to the user, the virtual patient including a plurality of health states;
receiving from the user at least one of a query for a medical finding concerning the instantiated virtual patient and a course of action; and
at least one one of;
generating, responsive to the received query, a specific medical finding at least in part from a first network defining a health state reveal structure corresponding to the instantiated virtual patient;
generating, responsive to the received query, an indication of an inappropriate query, based, at least in part, on a second network defining a medical practice management plan; and
generating, responsive to the received course of action, an indication of an inappropriate course of action, based, at least in part, on the second network. - View Dependent Claims (2)
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3. A computer system for evaluating or educating a user, compromising:
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a processor;
a computer-readable medium storing instructions executable by said processor, said instructions including at least one of;
generating a virtual patient based, at least in part, responsive to a description of a plurality of parallel health state networks;
generating the virtual patient based, at least in part, responsive to a description of rates of progression within and/or between the plurality of parallel health state networks; and
generating patient test data concerning the virtual patient, based, at least in part, using reveal structures to display of the patient test data to patient test data. - View Dependent Claims (4)
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5. A computer system for evaluating or educating a user, compromising:
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a processor;
a computer-readable medium storing instructions executable by said processor, said instructions including at least one of;
generating a virtual patient based, at least in part, based on a description of rates of progression within and/or between the plurality of parallel health state networks; and
generating patient test data concerning the virtual patient, based, at least in part, on reveal structures to display of the patient test data. - View Dependent Claims (6)
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7. A computer system for evaluating or educating a user, compromising:
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a processor;
a computer-readable medium storing instructions executable by said processor, said instructions including at least one of;
generating a virtual patient based, at least in part, on at least one of a plurality of parallel health state networks;
generating the virtual patient based, at least in part, on rates of progression within and/or between the at least one of the plurality of parallel health state networks; and
generating patient test data concerning the virtual patient, based, at least in part, on reveal structures.
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8. A computer readable medium including instructions being executed by a computer, the instructions instructing the computer to execute an educational or testing system for physicians, the instructions including:
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(a) accessing at least one representation, which describes at least one of a plurality of parallel health state networks;
(b) scripting a knowledge base, at least in part, from the at least one representation; and
(c) instantiating a model patient, at least in part, from the scripted knowledge base. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. A system for educating or evaluating a user comprising:
a model patient generator including a knowledge base scripted from at least one of at least one first network, which describes a plurality of parallel health state networks, and at least one second network, which describes at least one rate of progression within and/or between said plurality of parallel health state networks, and which describes at least one task factor that affects the at least one rate of progression. - View Dependent Claims (19, 20)
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21. A knowledge base module for an educational or testing system or an expert system, comprising at least one of:
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at least one first network, which describes each parallel health state network of a plurality of parallel health state networks;
at least one second network, which describes at least one rate of progression within and/or between said plurality of parallel health state networks, and which describes at least one task factor that affects the at least one rate of progression; and
at least one third network, which describes plan critiques including peer-accepted courses of action for addressing said plurality of parallel health state networks.
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Specification