US 12,424,325 B2
Systems and methods for remote controlled orthodontic treatment
Earl O. Bergersen, Glenview, IL (US)
Assigned to ORTHO-TAIN, INC., Toa Alta, PR (US)
Filed by ORTHO-TAIN, INC., Toa Alta, PR (US)
Filed on Sep. 1, 2023, as Appl. No. 18/460,079.
Prior Publication US 2025/0079001 A1, Mar. 6, 2025
Int. Cl. G16H 50/20 (2018.01); A61C 7/00 (2006.01); G16H 10/60 (2018.01)
CPC G16H 50/20 (2018.01) [A61C 7/002 (2013.01); G16H 10/60 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A system for remotely diagnosing and treating a patient by a neural network of an artificial intelligence engine, the system comprising:
one or more databases that retain historical data for a plurality of patients corresponding to a plurality of historical symptoms, a plurality of historical orthodontic treatment options, and a historical treatment efficiency for each of the plurality of historical orthodontic treatment options, each of the plurality of historical orthodontic treatment options corresponding to at least a combination of a number of historical symptoms of the plurality of historical symptoms and a severity of each of the number of historical symptoms;
at least one processor;
a memory device coupled to the at least one processor, the memory device including instructions that when executed by the at least one processor cause the at least one processor to:
determine a machine learning algorithm for patient diagnosis and treatment recommendations using historical data from the one or more databases for a plurality of patients corresponding to the plurality of historical symptoms, the plurality of historical orthodontic treatment options, and the historical treatment efficiency for each of the plurality of historical orthodontic treatment options, each of the plurality of historical orthodontic treatment options corresponding to at least a combination of a number of historical symptoms of the plurality of historical symptoms and a severity of each of the number of historical symptoms;
receive a patient captured information, the patient captured information being captured by the patient and comprising at least one image;
determine at least one measurement using the patient captured information;
identify at least a patient condition from the patient captured information;
analyze, for a continuous training of the machine learning algorithm, the historical data to identify one or more patterns that correlate the historical treatment efficiency for the plurality of historical orthodontic treatment options to the historical symptoms;
identify, using the at least one measurement and the patient condition, and by use of the machine learning algorithm, a recommended treatment option;
identify, in response to the recommended treatment option, an orthodontic apparatus;
generate a digital overlay comprising a digital placement of an orthodontic appliance image, corresponding to the orthodontic apparatus, on at least a portion of the at least one image;
determine, using the digital overlay, a size of the orthodontic apparatus relative to the portion of the at least one image;
select, for implementation, based at least in part on a result of the determination of the size of the orthodontic appliance image relative to the portion of the at least one image, the orthodontic apparatus for treatment of the patient;
generate an expected likelihood of success for the treatment of the patient based on at least the orthodontic apparatus selected for implementation, the patient condition, and the historical data from the one or more databases;
generate a signal to communicate the orthodontic apparatus selected for implementation and the expected likelihood of success to the dental detection communication device.