INTEGRATED MEDICAL PLATFORM

• US 20170011183A1
• Filed: 07/07/2015
• Published: 01/12/2017
• Est. Priority Date: 07/07/2015
• Status: Active Grant

• Current Assignee: Jonathan David Miller, L. James Valverde, Jr., Seven Medical Inc.
• Original Assignee: Seven Medical Inc.
• Inventors: Valverde, L. James Jr., Miller, Jonathan David, Miller, Harold Roy
• Granted Patent: US 10,332,631 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06F 40/295 Named entity recognition
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Provided is a system for automated medical decision-making. The system may include a first parser configured to parse text associated with medical information sources to obtain medical information and a second parser configured to parse patient data to obtain processed patient data. A processor, in communication with the first parser and the second parser, is configured to structure the medical information to form structured medical metadata in an intelligent medical database. Based on the structured medical metadata, the processor creates a causal network and receives the patient data from patient data sources. When the patient data is parsed by the second parser and the processed patient data is obtained, the processor maps the processed patient data against the causal network and generates the medical decision for the patient based on the mapping.

Claims

1. A computer-implemented method for automated medical decision-making, the method comprising:

parsing, by a first parser, text associated with one or more medical information sources to obtain medical information;

structuring, by a processor, the medical information to form structured medical metadata in an intelligent medical database, wherein the structured medical metadata comprises elements and relationships between the elements;

based on the structured medical metadata, creating, by the processor, a causal network, wherein the causal network includes a topological space with nodes and links between the nodes, the nodes representing the elements of the structured medical metadata and the links representing the relationships between the elements;

receiving, by the processor, patient data from one or more patient data sources;

parsing, by a second parser, the patient data to obtain processed patient data;

mapping, by the processor, the processed patient data against the causal network; and

based on the mapping, generating a medical decision for the patient.

2. The method of claim 1, wherein the elements of the structured medical metadata include one or more of the following:

a disease, a state, a cause, a symptom, a treatment, a test, an effect, an outcome, and an outlier.

4. The method of claim 1, further comprising:

weighting statistically, based on the patient data, the relationships between the elements of the structured medical metadata.

5. The method of claim 1, further comprising providing automated medical decision-making.

6. The method of claim 1, wherein the obtaining of the medical information from the one or more medical information sources includes using one or more of the following:

a metadata dictionary and a pattern recognition.

7. The method of claim 1, further comprising:

processing the patient data using an inference model and a pattern recognition.

8. The method of claim 1, further comprising:

retrieving, interpreting, and collating, by one or more grammar independent natural language parsers, the medical information from the one or more medical information sources.

3. (canceled)

9. A system for automated medical decision-making, the system comprising:

a first parser configured to parse text associated with one or more medical information sources to obtain medical information;

a second parser configured to parse patient data to obtain processed patient data; and

a processor in communication with the first parser and the second parser, the processor being configured to;

structure the medical information to form structured medical metadata in an intelligent medical database, wherein the structured medical metadata comprises elements and relationships between the elements;

create, based on the structured medical metadata, a causal network, wherein the causal network includes a topological space with nodes and links between the nodes, the nodes representing the elements of the structured medical metadata and the links representing the relationships between the elements;

receive the patient data from one or more patient data sources;

map the processed patient data against the causal network; and

generate, based on the mapping, a medical decision for the patient.

10. The system of claim 9, wherein the elements of the structured medical metadata include one or more of the following:

a disease, a state, a cause, a symptom, a treatment, a test, an effect, an outcome, and an outlier.

12. The system of claim 9, wherein the relationships between the elements of the structured medical metadata are weighted statistically based on the patient data.

13. The system of claim 9, wherein the first parser and the second parser include one or more grammar independent natural language parsers, the one or more grammar independent natural language parsers configured to retrieve, interpret, and collate the medical information from the one or more medical information sources.

14. The system of claim 9, wherein the medical information is obtained from the one or more medical information sources using one or more of the following:

a metadata dictionary and a pattern recognition.

15. The system of claim 14, wherein the metadata dictionary includes an equivalence class of terms and phrases associated with a medical lexicon.

16. The system of claim 14, wherein the metadata dictionary is captured using a bioinformatics ontology.

17. The system of claim 9, wherein the patient data is processed using an inference model and a pattern recognition.

18. The system of claim 9, wherein the patient data includes patient input in a form of a natural language.

19. The system of claim 9, wherein the patient data includes a text or a speech converted into text.

11. (canceled)

20. A system for automated medical decision-making, the system comprising:

a first parser configured to parse text associated with one or more medical information sources to obtain medical information;

a second parser configured to parse patient data to obtain processed patient data; and

a processor in communication with the first parser and the second parser, the processor being configured to;

structure the medical information to form structured medical metadata in an intelligent medical database, wherein the structured medical metadata comprises elements and relationships between the elements, wherein the elements of the structured medical metadata include one or more of the following;

a disease, a state, a cause, a symptom, a treatment, a test, an effect, an outcome, and an outlier;

create, based on the structured medical metadata, a causal network, wherein the causal network includes a topological space with nodes and links between the nodes, wherein the nodes represent the elements of the structured medical metadata and the links represent the relationships between the elements, the relationships between the elements of the structured medical metadata being weighted statistically based on the patient data;

receive the patient data from one or more patient data sources;

map the processed patient data against the causal network; and

generate, based on the mapping, a medical decision for the patient.