Hypothesis development based on selective reported events

• US 8,010,664 B2
• Filed: 05/28/2009
• Issued: 08/30/2011
• Est. Priority Date: 11/21/2008
• Status: Active Grant

• Current Assignee: Freede Solutions, Inc.
• Original Assignee: The Invention Science Fund I, L.L.C. (Intellectual Ventures LLC)
• Inventors: Firminger, Shawn P., Garms, Jason, Jung, Edward K. Y., Karkanias, Chris D., Leuthardt, Eric C., Levien, Royce A., Lord, Robert W., Malamud, Mark A., Rinaldo, Jr., John D., Tegreene, Clarence T., Tolle, Kristin M., Wood, JR., Lowell L.
• Primary Examiner(s): Gilles, Jude Jean
• Application Number:
  US12/455,309
• Publication Number:
  US 20100131449A1
• Time in Patent Office: 824 Days
• Field of Search: 709/224, 709/217
• US Class Current: 709/224
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06Q 90/00 Systems or methods specially adapted for administrative, commercial, financial, managerial or supervisory purposes, not involving significant data processing
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• 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
• CPC Class Codes: G16H 80/00 ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring

Abstract

A computationally implemented method includes, but is not limited to: acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user; determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and developing a hypothesis associated with the user based, at least in part, on the determined events pattern. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Claims

1. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user, wherein said means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user comprises;

means for receiving at least one of the data indicating incidence of a first one or more reported events and the data indicating incidence of a second one or more reported events;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern.

2. The computationally-implemented system of claim 1, wherein said means for receiving at least one of the data indicating incidence of a first one or more reported events and the data indicating incidence of a second one or more reported events comprises:

means for receiving at least one of the data indicating incidence of a first one or more reported events and the data indicating incidence of a second one or more reported events via one or more blog entries.

3. The computationally-implemented system of claim 1, wherein said means for receiving at least one of the data indicating incidence of a first one or more reported events and the data indicating incidence of a second one or more reported events comprises:

means for receiving at least one of the data indicating incidence of a first one or more reported events and the data indicating incidence of a second one or more reported events via one or more status reports.

4. The computationally-implemented system of claim 1, wherein said means for receiving at least one of the data indicating incidence of a first one or more reported events and the data indicating incidence of a second one or more reported events comprises:

means for receiving at least one of the data indicating incidence of a first one or more reported events and the data indicating incidence of a second one or more reported events via one or more electronic messages.

5. The computationally-implemented system of claim 1, wherein said means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events comprises:

means for determining the events pattern by excluding from the determination a third one or more reported events indicated by the events data.

6. The computationally-implemented system of claim 5, wherein said means for determining the events pattern by excluding from the determination a third one or more reported events indicated by the events data comprises:

means for filtering the events data to filter out data indicating incidence of the third one or more reported events.

7. The computationally-implemented system of claim 6, wherein said means for filtering the events data to filter out data indicating incidence of the third one or more reported events comprises:

means for filtering the events data based, at least in part, on historical data identifying and linking at least two event types.

8. The computationally-implemented system of claim 7, wherein said means for filtering the events data based, at least in part, on historical data identifying and linking at least two event types comprises:

means for filtering the events data by filtering out data that indicates events that are not identified by the historical data.

9. The computationally-implemented system of claim 6, wherein said means for filtering the events data to filter out data indicating incidence of the third one or more reported events comprises:

means for filtering the events data based, at least in part, on an existing hypothesis.

10. The computationally-implemented system of claim 9, wherein said means for filtering the events data based, at least in part, on an existing hypothesis comprises:

means for filtering the events data based, at least in part, on an existing hypothesis that is specific to the user.

11. The computationally-implemented system of claim 9, wherein said means for filtering the events data based, at least in part, on an existing hypothesis comprises:

means for filtering the events data based, at least in part, on an existing hypothesis that is associated with at least a subgroup of a general population, the user included in the subgroup.

12. The computationally-implemented system of claim 1, wherein said means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events comprises:

means for determining a time or temporal sequential pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events.

13. The computationally-implemented system of claim 1, wherein said means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events comprises:

means for determining a spatial pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events.

14. The computationally-implemented system of claim 1, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises:

means for creating the hypothesis based, at least in part, on at least the first one or more reported events and the second one or more reported events and on historical data.

15. The computationally-implemented system of claim 14, wherein said means for creating the hypothesis based, at least in part, on at least the first one or more reported events and the second one or more reported events and on historical data comprises:

means for creating the hypothesis based, at least in part, on historical data that is particular to the user.

16. The computationally-implemented system of claim 14, wherein said means for creating the hypothesis based, at least in part, on at least the first one or more reported events and the second one or more reported events and on historical data comprises:

means for creating the hypothesis based, at least in part, on historical data that is associated with at least a subgroup of a general population, the subgroup including the user.

17. The computationally-implemented system of claim 1, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises:

means for determining whether the determined events pattern supports an existing hypothesis associated with the user.

18. The computationally-implemented system of claim 17, wherein said means for determining whether the determined events pattern supports an existing hypothesis associated with the user comprises:

means for comparing the determined events pattern to an events pattern associated with the existing hypothesis to determine whether the determined events pattern supports the existing hypothesis.

19. The computationally-implemented system of claim 18, wherein said means for comparing the determined events pattern to an events pattern associated with the existing hypothesis to determine whether the determined events pattern supports the existing hypothesis comprises:

means for determining strength of the existing hypothesis associated with the user based, at least in part, on the comparison.

20. The computationally-implemented system of claim 17, wherein said means for determining whether the determined events pattern supports an existing hypothesis associated with the user comprises:

means for determining whether the determined events pattern supports an existing hypothesis that links a first event type with a second event type.

21. The computationally-implemented system of claim 20, wherein said means for determining whether the determined events pattern supports an existing hypothesis that links a first event type with a second event type comprises:

means for determining whether the determined events pattern supports an existing hypothesis that time or temporally links a first event type with a second event type.

22. The computationally-implemented system of claim 20, wherein said means for determining whether the determined events pattern supports an existing hypothesis that links a first event type with a second event type comprises:

means for determining whether the determined events pattern supports an existing hypothesis that spatially links a first event type with a second event type.

23. The computationally-implemented system of claim 1, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises:

means for developing a hypothesis that links a first subjective user state type with a second subjective user state type based, at least in part, on the determined events pattern.

24. The computationally-implemented system of claim 1, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises:

means for developing a hypothesis that links a first objective occurrence type with a second objective occurrence type based, at least in part, on the determined events pattern.

25. The computationally-implemented system of claim 1, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises:

means for developing a hypothesis that links a first subjective observation type with a second subjective observation type based, at least in part, on the determined events pattern.

26. The computationally-implemented system of claim 1, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises:

means for developing a hypothesis that associates one or more subjective user state types with one or more objective occurrence types based, at least in part, on the determined events pattern.

27. The computationally-implemented system of claim 1, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises:

means for developing a hypothesis that associates one or more subjective user state types with one or more subjective observation types based, at least in part, on the determined events pattern.

28. The computationally-implemented system of claim 1, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises:

means for developing a hypothesis that associates one or more objective occurrence types with one or more subjective observation types based, at least in part, on the determined events pattern.

29. The computationally-implemented system of claim 1, further comprising:

means for executing one or more actions in response to the developing.

30. The computationally-implemented system of claim 29, wherein said means for executing one or more actions in response to the developing comprises:

means for presenting one or more results of the developing.

31. The computationally-implemented system of claim 30, wherein said means for presenting one or more results of the developing comprises:

means for presenting the hypothesis.

32. The computationally-implemented system of claim 30, wherein said means for presenting one or more results of the developing comprises:

means for presenting an indication of a confirmation of the hypothesis.

33. The computationally-implemented system of claim 30, wherein said means for presenting one or more results of the developing comprises:

means for presenting an indication of soundness or weakness of the hypothesis.

34. The computationally-implemented system of claim 30, wherein said means for presenting one or more results of the developing comprises:

means for presenting an advisory of one or more past events.

35. The computationally-implemented system of claim 30, wherein said means for presenting one or more results of the developing comprises:

means for presenting a recommendation for a future action.

36. The computationally-implemented system of claim 29, wherein said means for executing one or more actions in response to the developing comprises:

means for monitoring of reported events.

37. The computationally-implemented system of claim 36, wherein said means for monitoring of reported events comprises:

means for monitoring of reported events to determine whether the reported events include events identified by the hypothesis.

38. The computationally-implemented system of claim 36, wherein said means for monitoring of reported events comprises:

means for monitoring of reported events being reported by the user.

39. The computationally-implemented system of claim 36, wherein said means for monitoring of reported events comprises:

means for monitoring of reported events being reported by one or more remote network devices.

40. The computationally-implemented system of claim 36, wherein said means for monitoring of reported events comprises:

means for monitoring of reported events being reported by one or more third party sources.

41. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events, wherein said means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events comprises;

means for determining the events pattern by excluding from the determination a third one or more reported events indicated by the events data; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern.

42. The computationally-implemented system of claim 41, wherein said means for determining the events pattern by excluding from the determination a third one or more reported events indicated by the events data comprises:

means for filtering the events data to filter out data indicating incidence of the third one or more reported events.

43. The computationally-implemented system of claim 42, wherein said means for filtering the events data to filter out data indicating incidence of the third one or more reported events comprises:

means for filtering the events data based, at least in part, on an existing hypothesis.

44. The computationally-implemented system of claim 43, wherein said means for filtering the events data based, at least in part, on an existing hypothesis comprises:

means for filtering the events data based, at least in part, on an existing hypothesis that is specific to the user.

45. The computationally-implemented system of claim 43, wherein said means for filtering the events data based, at least in part, on an existing hypothesis comprises:

means for filtering the events data based, at least in part, on an existing hypothesis that is associated with at least a subgroup of a general population, the user included in the subgroup.

46. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events, wherein said means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events comprises;

means for determining a time or temporal sequential pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern.

47. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events, wherein said means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events comprises;

means for determining a spatial pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern.

48. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises;

means for creating the hypothesis based, at least in part, on at least the first one or more reported events and the second one or more reported events and on historical data.

49. The computationally-implemented system of claim 48, wherein said means for creating the hypothesis based, at least in part, on at least the first one or more reported events and the second one or more reported events and on historical data comprises:

means for creating the hypothesis based, at least in part, on historical data that is particular to the user.

50. The computationally-implemented system of claim 48, wherein said means for creating the hypothesis based, at least in part, on at least the first one or more reported events and the second one or more reported events and on historical data comprises:

means for creating the hypothesis based, at least in part, on historical data that is associated with at least a subgroup of a general population, the subgroup including the user.

51. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises;

means for determining whether the determined events pattern supports an existing hypothesis associated with the user.

52. The computationally-implemented system of claim 51, wherein said means for determining whether the determined events pattern supports an existing hypothesis associated with the user comprises:

means for comparing the determined events pattern to an events pattern associated with the existing hypothesis to determine whether the determined events pattern supports the existing hypothesis.

53. The computationally-implemented system of claim 52, wherein said means for comparing the determined events pattern to an events pattern associated with the existing hypothesis to determine whether the determined events pattern supports the existing hypothesis comprises:

means for determining strength of the existing hypothesis associated with the user based, at least in part, on the comparison.

54. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises;

means for developing a hypothesis that links a first subjective user state type with a second subjective user state type based, at least in part, on the determined events pattern.

55. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises;

means for developing a hypothesis that links a first objective occurrence type with a second objective occurrence type based, at least in part, on the determined events pattern.

56. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises;

means for developing a hypothesis that links a first subjective observation type with a second subjective observation type based, at least in part, on the determined events pattern.

57. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises;

means for developing a hypothesis that associates one or more subjective user state types with one or more objective occurrence types based, at least in part, on the determined events pattern.

58. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises;

means for developing a hypothesis that associates one or more subjective user state types with one or more subjective observation types based, at least in part, on the determined events pattern.

59. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern, wherein said means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern comprises;

means for developing a hypothesis that associates one or more objective occurrence types with one or more subjective observation types based, at least in part, on the determined events pattern.

60. A computationally-implemented system in the form of a machine, article of manufacture, or composition of matter, comprising:

means for acquiring events data including data indicating incidence of a first one or more reported events and data indicating incidence of a second one or more reported events, at least one of the first one or more reported events and the second one or more reported events being associated with a user;

means for determining an events pattern based selectively on the incidences of the first one or more reported events and the second one or more reported events; and

means for developing a hypothesis associated with the user based, at least in part, on the determined events pattern; and

means for executing one or more actions in response to the developing.

61. The computationally-implemented system of claim 60, wherein said means for executing one or more actions in response to the developing comprises:

means for presenting one or more results of the developing.

62. The computationally-implemented system of claim 61, wherein said means for presenting one or more results of the developing comprises:

means for presenting an indication of soundness or weakness of the hypothesis.

63. The computationally-implemented system of claim 60, wherein said means for executing one or more actions in response to the developing comprises:

means for monitoring of reported events.

64. The computationally-implemented system of claim 63, wherein said means for monitoring of reported events comprises:

means for monitoring of reported events to determine whether the reported events include events identified by the hypothesis.