Dental data mining

• US 20050192835A1
• Filed: 02/27/2004
• Published: 09/01/2005
• Est. Priority Date: 02/27/2004
• Status: Active Grant

• Current Assignee: Align Technology Incorporated
• Original Assignee: Align Technology Incorporated
• Inventors: Kuo, Eric E., Overton, Christopher W., Nguyen, Cuong Van, Smedt, Philippe De
• Granted Patent: US 7,987,099 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: A61C 7/002 Orthodontic computer assisted systems
• CPC Class Codes: A61C 7/08 Mouthpiece-type retainers or positioners, e.g. for both the lower and upper arch arch-shaped medicament applicators for teeth or gums A61C19/063; mouthguards for protecting the teeth of sportsmen A63B71/085
• CPC Class Codes: B33Y 50/00 Data acquisition or data processing for additive manufacturing
• CPC Class Codes: B33Y 80/00 Products made by additive manufacturing
• CPC Class Codes: G06F 2216/03 Data mining
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

Systems and methods are disclosed providing a database comprising a compendium of at least one of patient treatment history; orthodontic therapies, orthodontic information and diagnostics; employing a data mining technique for interrogating said database for generating an output data stream, the output data stream correlating a patient malocclusion with an orthodontic treatment; and applying the output data stream to improve a dental appliance or a dental appliance usage.

Claims

1. A computer method comprising:

providing a database comprising a compendium of at least one of patient treatment history;

orthodontic therapies, orthodontic information and diagnostics;

employing a data mining technique for interrogating said database for generating an output data stream, the output data stream correlating a patient malocclusion with an orthodontic treatment; and

applying the output data stream to improve a dental appliance or a dental appliance usage.

2. The method of claim 1, further comprising generating a plurality of appliances having geometries selected to progressively reposition the teeth, wherein the appliances comprise polymeric shells having cavities and wherein the cavities of successive shells have different geometries shaped to receive and resiliently reposition teeth from one arrangement to a successive arrangement.

3. The method of claim 2, wherein the sequence of appliances includes a sequence of configurations of braces, the braces including brackets and archwires.

4. The method of claim 2, wherein the sequence of appliances includes a sequence of polymeric shells manufactured by fitting polymeric sheets over positive models corresponding to the teeth of the patient.

5. The method of claim 1, wherein the sequence of appliances includes a sequence of polymeric shells manufactured by stereo lithography from digital models

6. The method of claim 1, wherein the output data stream is related to clinical constraints.

7. The method of claim 6, wherein the clinical constraints include a maximum rate of displacement of a tooth, a maximum force on a tooth, and a desired end position of a tooth.

8. The method of claim 7, wherein the maximum force is a linear force or a torsional force.

9. The method of claim 7, wherein the maximum rate of displacement is a linear or a angular rate of displacement.

10. The method of claim 6, wherein the clinical constraints include a maximum rate of displacement of a tooth.

11. The method of claim 6, wherein the clinical constraints include a maximum rate of linear displacement of a tooth.

12. The method of claim 6, wherein the clinical constraints include a maximum rate of rotational displacement of a tooth.

13. The method of claim 1, wherein the last of the sequence of appliances is a positioner for finishing and maintaining teeth positions.

14. The method of claim 1, further comprising:

comparing an actual effect of the appliances with an intended effect of the appliances; and

identifying an appliance as an unsatisfactory appliance if the actual effect of the appliance is more than a threshold different from the intended effect of the appliance and modifying a model of the unsatisfactory appliance according to the results of the comparison.

15. The method of claim 1, further comprising capturing at least an initial tooth position, a target tooth position;

and one or more intermediate tooth positions.

16. The method of claim 1, further comprising analyzing one of the intermediate tooth positions with the target position.

17. The method of claim 1, further comprising capturing characteristics tags associated with a patient case to label captured data.

18. The method of claim 17, further comprising aggregating data of a set of treatments based on their tags and rating the set of treatments based on the aggregated data.

19. The method of claim 18, further comprising comparing performance of a plurality of sets of treatments.

20. The method of claim 1, further comprising applying models to calculate risk of treatment complications for individual patients.

21. The method of claim 20, further comprising identifying a treatment case for special handling.

22. The method of claim 20, further comprising identifying a treatment case for special treatment parameters including clinical constraint.

23. The method of claim 20, further comprising clusterizing clinical practitioners by practice habits.

24. The method of claim 23, wherein treatment parameters are adapted to preferences specific to each cluster.

25. The method of claim 1, further comprising applying probabilistic models to predict discrepancies between targeted and actual tooth position at given stages in treatment, and where said predictions are calculated into treatment plans.