Large-scale information collection and mining

• US 20070106626A1
• Filed: 11/04/2005
• Published: 05/10/2007
• Est. Priority Date: 11/04/2005
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Jojic, Nebojsa, Hinrichs, Randy, Heckerman, David, Mundie, Craig
• Granted Patent: US 7,406,453 B2
• Time in Patent Office: Days
• US Class Current: 706/20
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

The methods/systems described herein facilitate large-scale data collection and aggregation. One exemplary system that facilitates large-scale reporting of health-related data comprises a data collection component, a database and an aggregation component. The data collection component can collect health-related data on a large-scale from a non-selected population. The database can store at least some of the health-related data. The aggregation component can facilitate automatically ascertaining at least one pattern from the health-related data at least in part by applying one or more statistical, data-mining or machine-learning techniques to the database. One exemplary method of extracting health observations from information obtained on a macro-scale comprises receiving information about a plurality of self-selected subjects, pooling the information, mining the pooled information at least in part by employing a data-mining algorithm to infer one or more health observations from the pooled information, and monetizing the one or more health observations.

Claims

1. A system that facilitates large-scale reporting of health-related data, comprising:

a data collection component to collect health-related data on a large-scale relating to a non-selected population;

a database to store at least some of the health-related data; and

an aggregation component to facilitate automatically ascertaining at least one pattern from the health-related data, the aggregation component automatically ascertaining the at least one pattern from the health-related data at least in part by applying one or more of a statistical technique, a data mining technique and a machine-learning technique to the database.

2. The system of claim 1, wherein the health-related data is at least one of a drug-related event, a symptom, a device output, an activity, and patient-specific genetic information.

3. The system of claim 1, wherein the data collection component implicitly collects at least some of the health-related data.

4. The system of claim 1, wherein the data collection component automatically collects at least some of the health-related data.

5. The system of claim 1, wherein the data collection component collects at least some of the health-related data by prompting a user with at least one question.

6. The system of claim 5, wherein the data collection component determines one or more follow-up questions to present to the user based on the user'"'"'s answer to the at least one question.

7. The system of claim 1, wherein the one or more machine-learning techniques comprise an expectation-maximization algorithm.

8. The system of claim 1, wherein the data collection component comprises at least one of a free-text entry system, a bar-code reader, and a free-text entry system with intelligent spelling correction.

9. The system of claim 1, further comprising a forwarding component to forward the at least one pattern to a third party.

10. The system of claim 9, wherein the third party is charged a fee to receive the at least one pattern.

11. The system of claim 9, wherein the at least one pattern is forwarded to the third party via a data signal.

12. The system of claim 1, further comprising a reminder component to automatically send one or more alerts to a user.

13. The system of claim 1, wherein the data collection component employs a Human Interactive Proof.

14. The system of claim 1, wherein the data collection component anonymizes the health-related data.

15. The system of claim 1, wherein the data collection component and the aggregation component are encoded by computer-executable instructions stored on computer-readable media.

16. A method of extracting health observations from information obtained on a macro-scale, comprising:

receiving information about a plurality of self-selected subjects;

pooling the information;

mining the pooled information at least in part by employing one or more of a statistical algorithm, a data-mining algorithm and a machine-learning algorithm to infer one or more health observations from the pooled information; and

monetizing the one or more health observations.

17. The method of claim 16, further comprising providing at least some of the plurality of self-selected subjects with at least one incentive to self-select to supply information.

18. The method of claim 17, further comprising advertising the at least one incentive.

19. The method of claim 18, wherein advertising the at least one incentive comprises obtaining the rights to one or more health-related keywords on a search site.

20. An online system to facilitate global medical data analysis, comprising:

means for obtaining medical data from a global, unselected population via the Internet; and

means for automatically drawing conclusions from the medical data, the means for automatically drawing conclusions from the medical data employing one or more of a statistical algorithm, a machine-learning algorithm, a data-mining algorithm and an artificial-intelligence algorithm to draw at least one conclusion from the medical data.