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 system communicatable with a computer network, comprising:
- a server communicatable with a user via the computer network, said server being in communication with a processor and a computer-readable medium storing instructions executable by said processor, said instructions including;
(a) accessing a plurality of parallel health state networks describing at least one of a plurality of primary networks defining disease evolutions, a plurality of secondary networks defining risk factors affecting progression through a primary network of the plurality of primary networks, and a plurality of tertiary networks defining at least one of causal probabilistic medical complications attributed to at least one stage in the primary network and medical complications attributed to management of the at least one stage;
(b) accessing at least one first belief network which describes each of the plurality of parallel health state networks;
(c) accessing at least one second belief network which describes rates of progression within and/or between said plurality of parallel health state networks, and to describe task factors that affect the rates of progression;
(d) accessing at least one third belief network which supports plan critiques of queries of and treatment prescribed by the user;
(e) receiving patient;
(f) instantiating a virtual patient having characteristics consistent with the received patient data and based, at least in part, on the at least one first belief network and the at least one second belief network;
(g) generating one of a query to the user for a specific medical finding concerning the actual patient, and a course of action based, at least in part on the virtual patient and the at least one third belief network;
(h) receiving the specific medical finding from the user responsive to the generated query; and
(i) evolving the virtual patient in accordance with at least one of the at least one first belief network and the at least one second belief network, and responsive to the received specific medical finding.
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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.
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Citations
16 Claims
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1. A system communicatable with a computer network, comprising:
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a server communicatable with a user via the computer network, said server being in communication with a processor and a computer-readable medium storing instructions executable by said processor, said instructions including;
(a) accessing a plurality of parallel health state networks describing at least one of a plurality of primary networks defining disease evolutions, a plurality of secondary networks defining risk factors affecting progression through a primary network of the plurality of primary networks, and a plurality of tertiary networks defining at least one of causal probabilistic medical complications attributed to at least one stage in the primary network and medical complications attributed to management of the at least one stage;
(b) accessing at least one first belief network which describes each of the plurality of parallel health state networks;
(c) accessing at least one second belief network which describes rates of progression within and/or between said plurality of parallel health state networks, and to describe task factors that affect the rates of progression;
(d) accessing at least one third belief network which supports plan critiques of queries of and treatment prescribed by the user;
(e) receiving patient;
(f) instantiating a virtual patient having characteristics consistent with the received patient data and based, at least in part, on the at least one first belief network and the at least one second belief network;
(g) generating one of a query to the user for a specific medical finding concerning the actual patient, and a course of action based, at least in part on the virtual patient and the at least one third belief network;
(h) receiving the specific medical finding from the user responsive to the generated query; and
(i) evolving the virtual patient in accordance with at least one of the at least one first belief network and the at least one second belief network, and responsive to the received specific medical finding. - View Dependent Claims (2, 3)
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4. A system communicatable with a computer network, comprising:
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a server communicatable with a user via the computer network, said server being in communication with a processor and a computer-readable medium storing instructions executable by said processor, said instructions including;
(a) accessing a plurality of parallel health state networks describing at least one of a plurality of primary networks defining disease evolutions, a plurality of secondary networks defining risk factors affecting progression through a primary network of the plurality of primary networks, and a plurality of tertiary networks defining at least one of causal probabilistic medical complications attributed to at least one stage in the primary network and medical complications attributed to management of the at least one stage;
(b) accessing at least one first belief network which describes each of the plurality of parallel health state networks;
(c) accessing at least one second belief network which describes rates of progression within and/or between said plurality of parallel health state networks, and to describe task factors that affect the rates of progression;
(d) accessing at least one third belief network which support reveal structures to limit display of patient test data to patient test data specifically requested by the user;
(e) accessing at least one fourth belief network which supports plan critiques of queries of and treatment prescribed by the user;
(f) scripting a knowledge base from the at least one first belief network and the at least one second belief network;
(g) instantiating a model patient based, at least in part, from the scripted knowledge base;
(h) receiving one of a course of action and a query for a specific medical finding concerning the model patient from the user responsive to the instantiated model patient;
(i) displaying, if the query is received, the specific medical finding to the user based at least in part on the at least one third belief network, and repeating the instruction (h); and
(j) evolving the model patient in accordance with at least one of the at least one first belief network and the at least one second belief network and responsive to the received course of action. - View Dependent Claims (5, 6)
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7. A computer network appliance comprising:
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a thin client programmably connected via a computer network to a single web hosting facility, the single web hosting facility including a server communicatable with a user via the computer network, said server being in communication with a processor and a computer-readable medium storing instructions executable by said precessor, said instructions including;
(a) accessing a plurality of parallel health state networks describing at least one of a plurality of primary networks defining disease evolutions, a plurality of secondary networks defining risk factors affecting progression through a primary network of the plurality of primary networks, and a plurality of tertiary networks defining at least one of causal probabilistic medical complications attributed to at least one stage in the primary network and medical complications attributed to management of the at least one stage;
(b) accessing at least one first belief network, which describes each of the plurality of parallel health state networks;
(c) accessing at least one second belief network, which describes rates of progression within and/or between said plurality of parallel health state networks, and describes task factors that affect the rates of progression;
(e) accessing at least one third belief network, which supports plan critiques of queries of and treatment prescribed by the user;
(f) receiving patient data;
(g) instantiating a virtual patient having characteristics consistent with the received patient data and based, at least in part, on at least one of the at least one first belief network and the at least one second belief network;
(h) generating one of a query to the user for a specific medical finding concerning the actual patient, and a course of action based, at least in part on the virtual patient and the at least one third belief network;
(i) receiving the specific medical finding from the user responsive to the generated query; and
(j) evolving the virtual patient in accordance with at least one of the at least one first belief network and the at least one second belief network, and responsive to the received specific medical finding. - View Dependent Claims (8, 9)
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10. 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
one of;
generating, responsive to the received query, a specific medical finding at least in part from a first causal probability 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 causal probability 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 causal probability network. - View Dependent Claims (11)
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12. 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 first belief network, which describes a plurality of parallel health state networks;
generating the virtual patient based, at least in part, on at least one second belief network, which describes 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 at least one third belief network, which supports reveal structures to limit display of the patient test data to patient test data specifically requested by the user. - View Dependent Claims (13)
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14. 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 causal probabilistic network, which describes rules 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 the at least one causal probabilistic network, which supports reveal structures to limit display of the patient test data to patient test data specifically requested by the user. - View Dependent Claims (15)
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16. 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 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 plurality of parallel health state networks; and
generating patient test data concerning the virtual patient, based, at least in part, on reveal structures limiting display of the patient test data requested by the user.
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Specification