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

• US 9,517,111 B2
• Filed: 08/20/2015
• Issued: 12/13/2016
• 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): Smith, Paulinho E
• Application Number:
  US14/831,648
• Publication Number:
  US 20150351870A1
• Time in Patent Office: 481 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0088 for oral or dental tissue
• CPC Class Codes: A61B 5/4547 Evaluating teeth
• CPC Class Codes: A61B 5/4552 Evaluating soft tissue within the mouth, e.g. gums or tongue
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: A61C 19/05 for determining occlusion
• CPC Class Codes: A61C 7/002 Orthodontic computer assisted systems
• CPC Class Codes: G06F 16/24 Querying
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• 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 10/60 for patient-specific data, e.g. for electronic patient records
• 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

Abstract

A method for treating an orthodontic condition can include receiving patient data, such as through a website, accessing a database having information derived from patient treatments, generating a model of an orthodontic condition defining one or more anatomic features of a set of teeth, identifying a diagnosis of an orthodontic condition and identifying a treatment regimen for the diagnosis. A method can include tagging an anatomic feature with an electronic identifier and automatically generating a tooth setup. A system can include a server and a database, which can include information relating to patient treatments, and a website for receiving patient data. A system can include an electronic model representing anatomic features of a patient'"'"'s teeth and an application adapted to identify a diagnosis and a treatment regimen for an orthodontic condition, which can include executing artificial intelligence and/or other algorithms.

Claims

1. A method for delivering a diagnosis and identification of a treatment for an orthodontic condition, comprising:

providing a graphical user interface that prompts a user for electronic patient data regarding the orthodontic condition;

providing access, through the graphical user interface, to a database that comprises or has access to information derived from patient treatments, the information derived from patient treatments including an electronically stored data set for each patient treatment, wherein each data set includes data that represents at least one of (a) a location and position of one or more teeth subject of a corresponding patient treatment and (b) a previously diagnosed orthodontic condition for the corresponding patient treatment;

comparing coordinates that represent at least two anatomic features of a set of teeth to at least a portion of the information derived from patient treatments accessible via the database;

identifying a best fit data set that represents a statistical or prioritized best fit for the coordinates;

identifying at least one diagnosis of the orthodontic condition by prioritizing at least a portion of the data from a plurality of the data sets; and

delivering an electronic treatment model of the orthodontic condition that provides to the user one or more of (a) a diagnosis, (b) the diagnosis along with a probability value representing a likelihood the diagnosis is accurate, and (c) a plurality of diagnoses along with a plurality of probability values.

2. The method of claim 1, wherein each of the plurality of probability values represents a likelihood that a corresponding one of the plurality of diagnoses is accurate.

3. The method of claim 1, further comprising identifying at least one treatment regimen for the at least one diagnosis by prioritizing at least a portion of the data from a plurality of the data sets, and delivering an electronic treatment model of the orthodontic condition that provides to the user one or more of (a) a treatment regimen, (b) the treatment regimen along with a probability value representing a likelihood the treatment regimen is accurate, and (c) a plurality of treatment regimens along with a plurality of probability values.

4. The method of claim 3, wherein each of the plurality of probability values represents a likelihood that a corresponding one of the plurality of treatment regimens is accurate.

5. The method of claim 3, wherein the at least one treatment regimen for the at least one diagnosis includes at least one of a treatment approach, a corrective appliance and a combination thereof.

6. The method of claim 3, further comprising outputting to the user a plurality of treatment regimens along with a plurality of probability values, wherein each of the plurality of probability values represents a relative likelihood that a corresponding one of the potential treatment regimens will be effective to reorient one or more teeth of the set of teeth represented in the electronic treatment model, and wherein the plurality of treatment regimens include at least one of interproximal tooth reduction, tooth extraction, tooth restoration and a combination thereof.

7. The method of claim 3, wherein the information derived from patient treatments includes data representing treatment time for one or more patient treatments and the method further comprises outputting to the user at least one of an estimated treatment time and an average treatment time for the at least one treatment regimen.

8. The method of claim 3, wherein at least one of the at least one diagnosis and the at least one treatment regimen is the same as that for a patient treatment corresponding to the best fit data set.

9. The method of claim 1, further comprising prompting the user to tag one or more of the at least two anatomic features with an electronic identifier.

10. The method of claim 1, further comprising outputting to the user a malocclusion classification for the orthodontic condition along with a probability value representing a likelihood the malocclusion classification is accurate.

11. The method of claim 1, further comprising aligning the at least two anatomic features based on a pattern representing a target orthodontic condition, wherein the target orthodontic condition is at least one of an ideal condition, an acceptable condition based on a consensus of previously successful patient treatments and a combination thereof.

12. The method of claim 1, further comprising aligning the at least two anatomic features at least one of:

along a curve, along a spline, relative to one or more additional anatomic features of a set of teeth, and a combination thereof.

13. The method of claim 1, wherein a first of the at least two anatomic features is on a first arch and a second of the at least two anatomic features is on a second arch, the method further comprising aligning the first anatomic feature on the first arch relative to the second anatomic feature on the second arch.

14. The method of claim 1, further comprising providing the graphical user interface via a wireless interface.

15. The method of claim 1, further comprising wherein the database comprises or has access to patient treatment information derived from at least one of textbooks, scientific literature, results derived from ongoing patient treatments, results derived from completed patient treatments, and a combination thereof.

16. The method of claim 1, further comprising wherein the coordinates that represent the at least two anatomic features of a set of teeth are three-dimensional coordinates.

17. An orthodontic diagnostic and treatment system, comprising:

a data interface configured to access information derived from patient treatments, the information derived from patient treatments including an electronically stored data set for each of a plurality of patient treatments, wherein each data set includes data that represents at least one of (a) a location and position of one or more teeth subject of a corresponding patient treatment, (b) a previously diagnosed orthodontic condition for the corresponding patient treatment, and (c) an electronic treatment model of the orthodontic condition that includes coordinates that represent at least two anatomic features of a set of teeth; and

a management node configured to receive electronic patient data of a user and to retrieve information derived from patient treatments through the data interface, the management node including means for comparing coordinates of the electronic patient data of the user to at least a portion of the information derived from patient treatments, for identifying a best fit data set that represents a statistical or prioritized best fit for the coordinates, for identifying at least one diagnosis of an orthodontic condition by prioritizing at least a portion of the data from a plurality of the data sets, and for outputting to the user one or more of (a) a diagnosis, (b) the diagnosis along with a probability value representing a likelihood the diagnosis is accurate, and (c) a plurality of diagnoses along with a plurality of probability values, wherein each of the plurality of probability values represents a likelihood that a corresponding one of the plurality of diagnoses is accurate.

18. The system of claim 17, further comprising means for identifying at least one treatment regimen for the at least one diagnosis by prioritizing at least a portion of the data from a plurality of the data sets, and for outputting to the user one or more of (a) a treatment regimen, (b) the treatment regimen along with a probability value representing a likelihood the treatment regimen is accurate, and (c) a plurality of treatment regimens along with a plurality of probability values, wherein each of the plurality of probability values represents a likelihood that a corresponding one of the plurality of treatment regimens is accurate.

19. The system of claim 18, wherein the at least one treatment regimen for the at least one diagnosis includes at least one of a treatment approach, a corrective appliance and a combination thereof.

20. The system of claim 17, further comprising wherein the coordinates of the electronic patient data of the user are three-dimensional coordinates.