Methods and systems for employing artificial intelligence in automated orthodontic diagnosis and treatment planning

• US 8,856,053 B2
• Filed: 06/28/2013
• Issued: 10/07/2014
• Est. Priority Date: 03/17/2010
• Status: Active Grant

• Current Assignee: ClearCorrect Holdings LLC (ClearCorrect Incorporated)
• Original Assignee: ClearCorrect Holdings LLC (ClearCorrect Incorporated)
• Inventors: Mah, James
• Primary Examiner(s): Gaffin, Jeffrey A
• Assistant Examiner(s): Smith, Paulinho E
• Application Number:
  US13/930,353
• Publication Number:
  US 20130297554A1
• Time in Patent Office: 466 Days
• Field of Search: None
• US Class Current: 706/12
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/048 Fuzzy inferencing
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• 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 70/60 relating to pathologies

Abstract

Methods and systems for diagnosing and identifying a treatment for an orthodontic condition can include a server configured to receive patient data through a website. Methods and systems can include the use of a database that includes or has access to information derived from textbooks and scientific literature and dynamic results derived from ongoing and completed patient treatments. Methods and systems can include the operation of at least one computer program within the server, which can be capable of analyzing patient data and identifying at least one diagnosis of an orthodontic condition. Methods and systems can include assigning a probability value to at least one diagnosis, and the probability value can represent a likelihood that a diagnosis is accurate. Methods and systems can include instructing a computer program to identify at least one treatment approach, a corrective appliance, or a combination thereof for the at least one diagnosis.

Claims

1. A method for diagnosing and identifying a treatment for an orthodontic condition, comprising:

providing a server on which a website is hosted, wherein the server is configured to receive patient data through the website;

providing a database that comprises or has access to information derived from textbooks and scientific literature and dynamic results derived from ongoing and completed patient treatments;

instructing at least one computer program within the server to analyze the patient data and identify at least one diagnosis of the orthodontic condition based on said information derived from textbooks and scientific literature and dynamic results derived from ongoing and completed patient treatments;

executing an artificial intelligence algorithm based on one or more inputs derived from at least one of the patient data, the information derived from textbooks and scientific literature and the dynamic results derived from ongoing and completed patient treatments;

assigning a probability value to the at least one diagnosis, wherein the probability value represents a likelihood that the diagnosis is accurate; and

instructing the computer program to identify at least one treatment regimen for the at least one diagnosis, the at least one treatment regimen including at least one of a treatment approach, a corrective appliance and a combination thereof.

2. The method of claim 1, further comprising identifying a location and position of one or more of a plurality of teeth in the patient data in at least one of two-dimensional space and three-dimensional space and assigning coordinates to at least one of the plurality of teeth, wherein said coordinates are correlated to a location and position of the at least one tooth.

3. The method of claim 2, further comprising:

instructing the server to identify a diagnostic data set contained within said database which represents a statistical best fit, or most closely resembles, the coordinates for the at least one tooth of the patient; and

instructing the server to diagnose the orthodontic condition based on the diagnostic data set.

4. The method of claim 2, wherein the probability value that is assigned to the at least one diagnosis is based, at least in part, on a confidence level that has been assigned to a diagnostic data set which the server identifies as a statistical best fit for the coordinates for the at least one tooth of the patient.

5. The method of claim 1, further comprising instructing the server to calculate a probability value that is correlated with a relative likelihood of the at least one treatment regimen being effective to reorient at least one tooth of the patient.

11. The method of claim 1, further comprising estimating a treatment time for the at least one treatment regimen.

12. The method of claim 1, further comprising wherein the one or more inputs include at least one utility value that indicates a relative importance of a treatment parameter versus one or more other treatment parameters.

13. The method of claim 1, further comprising wherein the artificial intelligence algorithm utilizes at least one of statistical estimation methodology, optimization methodology, control theory methodology and a combination thereof.

6. A system for diagnosing and identifying a treatment for an orthodontic condition, comprising:

a server on which a website is hosted, wherein the server is configured to receive patient data through the website;

a database that comprises or has access to information derived from textbooks and scientific literature and dynamic results derived from ongoing and completed patient treatments; and

at least one computer program housed within or accessible by the server and capable of analyzing the patient data and identifying at least one diagnosis of the orthodontic condition based on said information derived from textbooks and scientific literature and dynamic results derived from ongoing and completed patient treatments, wherein the server is configured to;

execute an artificial intelligence algorithm based on one or more inputs derived from at least one of the patient data, the information derived from textbooks and scientific literature and the dynamic results derived from ongoing and completed patient treatments;

assign a probability value to the at least one diagnosis, wherein the probability value represents a likelihood that the diagnosis is accurate; and

instruct the computer program to identify at least one treatment regimen, the at least one treatment regimen including at least one of a treatment approach, a corrective appliance and a combination thereof.

7. The system of claim 6, wherein the server is further configured to identify a location and position of one or more of a plurality of teeth in the patient data in at least one of two-dimensional space and three-dimensional space and assign coordinates to at least one of the plurality of teeth, wherein said coordinates are correlated to the location and position of the at least one tooth.

8. The system of claim 7, wherein the server is further configured to:

identify a diagnostic data set contained within said database which represents a statistical best fit, or most closely resembles, the coordinates for the at least one tooth of the patient; and

diagnose the orthodontic condition based on the diagnostic data set.

9. The system of claim 7, wherein the probability value that is assigned to the at least one diagnosis is based, at least in part, on a confidence level that has been assigned to a diagnostic data set which the server identifies as a statistical best fit for the coordinates for the at least one tooth of the patient.

10. The system of claim 6, wherein the server is further configured to calculate a probability value that is correlated with a relative likelihood of the at least one treatment regimen being effective to reorient at least one tooth of the patient.

14. The system of claim 6, further comprising wherein the server is configured to estimate a treatment time for the at least one treatment regimen.

15. The system of claim 6, further comprising wherein the one or more inputs include at least one utility value that indicates a relative importance of a treatment parameter versus one or more other treatment parameters.

16. The system of claim 6, further comprising wherein the artificial intelligence algorithm utilizes at least one of statistical estimation methodology, optimization methodology, control theory methodology and a combination thereof.

17. A non-transitory computer readable medium having instructions stored thereon that, when executed by a processor, cause the processor to perform a method comprising:

receiving patient data from a server on which a website is hosted;

receiving information from a database that comprises or has access to

information derived from textbooks and scientific literature and dynamic results derived from ongoing and completed patient treatments;

analyzing the patient data and identifying at least one diagnosis of the orthodontic condition based on the information derived from textbooks and scientific literature and the dynamic results derived from ongoing and completed patient treatments;

executing an artificial intelligence algorithm based on one or more inputs derived from at least one of the patient data, the information derived from textbooks and scientific literature and the dynamic results derived from ongoing and completed patient treatments;

assigning a probability value to the at least one diagnosis, wherein the probability value represents a likelihood that the diagnosis is accurate; and

identifying at least one treatment regimen for the at least one diagnosis, the at least one treatment regimen including at least one of a treatment approach, a corrective appliance and a combination thereof.

18. The non-transitory computer readable medium of claim 17, wherein the probability value that is assigned to the at least one diagnosis is based, at least in part, on a confidence level that has been assigned to a diagnostic data set which the server identifies as a statistical best fit for coordinates assigned to at least one tooth of the patient, the coordinates correlating to a location and position of the at least one tooth.

19. The non-transitory computer readable medium of claim 17, further comprising calculating a probability value that is correlated with a relative likelihood of the at least one treatment regimen being effective to reorient at least one tooth of the patient.

20. The non-transitory computer readable medium of claim 17, further comprising wherein the one or more inputs include at least one utility value that indicates a relative importance of a treatment parameter versus one or more other treatment parameters.