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Application US20180218790
Published 2018-08-02
Artificial General Intelligence System And Method For Medicine
A medical general intelligence computer system and computer-implemented methods analyze morpho-physiological numbers for determining a risk of an emergent disease state, determining an emergent disease state, predicting a pre-emergent disease state, determining a pre-emergent disease state, and/or predicting a risk of a pre-emergent disease state.
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- 1. A computer-implemented method for determining a disease state the method comprising: a processor accessing from a computer-readable memory, computer-readable data representing a general graph having nodes of physiological conditions, wherein each of the physiological conditions is represented by each of the nodes, wherein each of the nodes is connected by one or more edges representing correlations between the nodes; the processor accessing from the computer-readable memory, computer-readable data of physiological conditions of a patient; the processor executing computer-readable instructions for quantification of the physiological conditions of the patient; the processor transforming the physiological conditions of the patient to node data by performing quantification of the physiological conditions of the patient; the processor executing computer-readable instructions for associating the node data to the general graph; the processor creating an individualized graph by associating the node data to the general graph; the processor storing the individualized graph to the computer-readable memory; the processor accessing from the computer-readable memory, computer-readable data representing a topological module of nodes connected by edges, wherein the topological module represents the disease state; and the processor executing computer-readable instructions for mapping the topological module to the individualized graph.
- 4. A computer-implemented method for creating a graph for determining a disease state, the method comprising: storing on a computer-readable memory, computer-readable data representing a general graph of physiological conditions, wherein each of the physiological conditions is represented as a node of the general graph, wherein each node is connected by one or more edges representing correlations between the nodes; and storing on the computer-readable memory, computer-readable data representing a topological module of nodes connected by edges, wherein the topological module represents the disease state, and the topological module can be mapped on to a portion of the general graph.
- 5. A computer-implemented method for determining a pre-emergent disease state, the method comprising: a processor accessing from a computer-readable memory, computer-readable data representing physiological conditions represented as nodes, wherein at least one of the nodes has a correlation to another one of the nodes; the processor accessing from the computer-readable memory, computer-readable data of first physiological conditions of a patient collected at a first time period; the processor transforming the first physiological conditions of the patient to first node data by performing quantification of the first physiological conditions of the patient; the processor accessing from the computer-readable memory, computer-readable data of second physiological conditions of the patient collected at a second time period; the processor transforming the second physiological conditions of the patient to second node data by performing quantification of the second physiological conditions of the patient; the processor accessing from the computer-readable memory, computer-readable data representing a topological module of nodes, wherein the topological module represents the pre-emergent disease state; the processor mapping the topological module to the first node data; the processor mapping the topological module to the second node data; and the processor determining the pre-emergent disease state based on the mapping the topological module to the first node data and to the second node data.
- 6. (canceled)
