SYSTEM AND METHOD FOR DIAGNOSIS INVOLVING CROWDSOURCING

• US 20130253940A1
• Filed: 03/20/2012
• Published: 09/26/2013
• Est. Priority Date: 03/20/2012
• Status: Abandoned Application

• Current Assignee: Zilla Collections LLC
• Original Assignee: Zilla Collections LLC
• Inventors: Zziwa, Aloysious
• Application Number:
  US13/425,009
• Publication Number:
  US 20130253940A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• 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 70/60 relating to pathologies
• 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
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A system and method for diagnosing a condition or problem (including but not limited to health-related conditions) includes at least one computing device configured to perform steps including collecting and storing electronic data from a search user seeking to obtain diagnosis, applying stored diagnosis rules to the electronic data to identify possible diagnoses each having an associated diagnosis rule trust factor and based on information received from expert users and non-preselected contributing users, and communicating multiple of possible diagnoses based at least in part on diagnosis rule trust factors. User feedback and data mining applied to search data may also be used to help a learning engine improve diagnosis results over time.

Claims

1. A system for diagnosing a condition or problem, the system comprising:

a communication interface for sending and receiving network messages; and

a control module coupled with the communication interface configured to;

collect and store electronic data from a search user seeking to obtain diagnosis of the condition or problem, wherein the electronic data includes information indicative of at least one symptom relating to the condition or problem and includes information indicative of geographic region or location of the search user;

apply stored diagnosis rules to the electronic data to identify at least one possible diagnosis of the condition or problem, wherein the stored diagnosis rules includes diagnosis rules generated from information contributed by any of (i) expert users and (ii) non-preselected contributing users, and wherein each diagnosis rule has associated therewith a diagnosis rule trust factor; and

communicate to the search user the identified at least one possible diagnosis of the condition or problem.

2. A system according to claim 1, wherein the control module comprises a learning engine configured to perform at least one of the following tasks:

(i) infer diagnosis rules generated from information contributed by any of expert users and non-preselected contributing users;

(ii) categorize diagnosis rules;

(iii) adjust diagnosis rule trust factors associated with diagnosis rules;

(iv) promote provisional diagnosis rules to confirmed diagnosis rules eligible for application to the electronic data to identify at least one possible diagnosis of the condition or problem; and

(v) demote confirmed diagnosis rules to provisional diagnosis rules not eligible for application to the electronic data to identify at least one possible diagnosis of the condition or problem.

3. A system according to claim 1, wherein the control module is configured to elicit feedback from a search user via the communication interface, wherein the feedback is indicative of accuracy or perceived accuracy of the at least one possible diagnosis, wherein the control module is configured to adjust at least one diagnosis rule trust factor based on search user feedback regarding accuracy or perceived accuracy of diagnoses generated by applying the stored diagnosis rules, and to store the adjusted at least one diagnosis rule trust factor.

4. A system according to claim 1, wherein the control module is configured to access a first database including provisional diagnosis rules that are not eligible for application to the electronic data to identify at least one possible diagnosis of the condition or problem, and the control module is configured to access a second database including confirmed diagnosis rules that are eligible for application to the electronic data to identify at least one possible diagnosis of the condition or problem.

5. A system according to claim 1, wherein the control module is configured to:

receive, from a non-preselected contributing user, electronic data including information indicative of at least one symptom of a condition or problem, and indicative of a diagnosis of the condition or problem corresponding to the at least one symptom;

generate a new diagnosis rule based on the information received from the non-preselected contributing user;

associate a diagnosis rule trust factor with the new diagnosis rule; and

apply the new diagnosis rule in conjunction with the stored diagnosis rules to the electronic data collected from the search user to identify a plurality of possible diagnoses of the condition or problem.

6. A system according to claim 1, wherein the control module comprises a learning engine configured to:

analyze stored information contributed by any of contributing users and expert users, and

based on the analyzed information, perform any of the following;

(i) generate new diagnosis rules, (ii) modify existing diagnosis rules, (iii) generate symptom descriptions, and (iv) modify existing symptom descriptions.

7. A system according to claim 1, wherein:

the condition or problem includes a disease; and

the control module is configured to identify trends of diagnosis results relating to the disease, and configured to report to at least one health authority information indicative of an increased temporal and/or geographic incidence of diagnosis results relating to the disease.

8. A system according to claim 1, wherein the condition or problem includes at least one of the following:

a medical condition, a disease, a drug interaction, and a drug side effect.

9. A method for diagnosing a condition or problem, method comprising utilizing at least one computing device that includes at least one processor and at least one memory element, to perform steps comprising:

collecting and storing electronic data from a search user seeking to obtain diagnosis of the condition or problem, wherein the electronic data includes information indicative of at least one symptom relating to the condition or problem and includes information indicative of geographic region or location of the search user;

applying stored diagnosis rules to the electronic data to identify at least one possible diagnosis of the condition or problem, wherein the stored diagnosis rules includes diagnosis rules generated from information contributed by any of (i) expert users and (ii) non-preselected contributing users, and wherein each diagnosis rule has associated therewith a diagnosis rule trust factor; and

communicating to the search user the identified at least one possible diagnosis of the condition or problem.

10. A method according to claim 9, wherein said at least one possible diagnosis of the condition or problem comprises a plurality of possible diagnoses of the condition or problem, and wherein said communicating to the search user includes ranking possible diagnoses of the plurality of possible diagnoses based at least in part on diagnosis rule trust factors associated with the diagnosis rules used to identify the respective possible diagnoses.

11. A method according to claim 10, wherein said ranking of possible diagnoses is based in part on said information indicative of geographic region or location of the search user.

12. A method according to claim 9, further comprising eliciting feedback from the search user indicative of accuracy or perceived accuracy of the at least one possible diagnosis.

13. A method according to claim 9, further comprising adjusting at least one diagnosis rule trust factor based on search user feedback regarding accuracy or perceived accuracy of diagnoses generated by applying the stored diagnosis rules, and storing the adjusted at least one diagnosis rule trust factor in the at least one memory element.

14. A method according to claim 9, wherein said collecting of electronic data comprises:

presenting the search user with at least one demonstrative item representative of a symptom potentially related to the condition or problem, the demonstrative item comprising any of (i) a photographic image, (ii) a sound clip, (iii) a video clip, and (iv) a diagnostic scanning image; and

eliciting information from the search user indicative of at least one symptom of the condition or problem based on the search user'"'"'s review of the at least one demonstrative item.

15. A method according to claim 9, wherein said collecting of electronic data comprises suggesting to a search user at least one potential additional symptom based on any one or more of:

(i) electronic data collected from a search user indicative of at least one symptom relating to the condition or problem, (ii) information indicative of geographic region or location of the search user, (iii) at least one possible diagnosis previously communicated to the search user, and (iv) search user feedback based on at least one possible diagnosis communicated identified to the search user.

16. A method according to claim 9, further comprising, based on at least one possible diagnosis of the condition or problem identified to the search user, providing the search user with contact information for, or initiating communication by the search user with, any one or more of the following:

(i) at least one expert user having expertise relating to the problem or condition, (ii) at least one provider of treatment or mitigation services relating to the problem or condition, and (iii) at least one provider of treatment or mitigation products relating to the problem or condition.

17. A method according to claim 9, further comprising:

receiving, from a non-preselected contributing user, electronic data including information indicative of at least one symptom of a condition or problem, and indicative of a diagnosis of the condition or problem corresponding to the at least one symptom;

generating a new diagnosis rule based on the information received from the non-preselected contributing user;

associating a diagnosis rule trust factor with the new diagnosis rule; and

applying the new diagnosis rule in conjunction with the stored diagnosis rules to the electronic data collected from the search user to identify a plurality of possible diagnoses of the condition or problem.

18. A method according to claim 9, wherein the condition or problem includes at least one of the following:

a medical condition, a disease, a drug interaction, and a drug side effect.

19. A method according to claim 9, wherein the condition or problem includes a disease, and the method further comprises:

identifying trends of diagnosis results relating to the disease, and reporting to at least one health authority information indicative of an increased temporal and/or geographic incidence of diagnosis results relating to the disease.

20. A method for diagnosing a condition or problem, method comprising utilizing at least one computing device that includes at least one processor and at least one memory element, to perform steps comprising:

collecting and storing electronic data from a search user seeking to obtain diagnosis of the condition or problem, wherein the electronic data includes information indicative of at least one symptom relating to the condition or problem and includes information indicative of geographic region or location of the search user;

applying stored diagnosis rules to the electronic data to identify a plurality of possible diagnoses of the condition or problem, wherein each diagnosis rule has associated therewith a diagnosis rule trust factor; and

communicating to the search user the plurality of possible diagnoses of the condition or problem, wherein such identifying includes ranking the possible diagnoses based at least in part on diagnosis rule trust factors associated with the diagnosis rules used to identify the respective possible diagnoses.