AI software which assesses occlusal and dental changes through a series of intra-oral photographs taken by the patient using their smartphone 

Upload STL / digital study model

Ai segmentation of teeth which maps digital study model to the photos

Aligner fit analysis:

Discrepancy between tooth surface and aligner fit 

Either proceed, continue wear or see clinician

Fixed appliances 

Assess rate of movement and schedule appointment

Other proposed benefits

Oral hygiene assessment

Breakages

Retention changes

81% interested in reducing number of appointments due to telemonitoring – Dalessandri 2021

25% of patients found scans difficult to perform, with duration of scan 2-17 minutes Hansa 2020

Decrease the number of in-office visits by 1.68–3.5 visits 

No difference in treatment duration 

No statistical reduction in emergency appointments

No difference in tooth movements  Hansa 2021

No difference in number of refinements  Hansa 2021

PAR changes – no difference in quality of outcomes Jarad Marks 2024

DM reduced plaque scores Costi 2019

31% Improved hygiene  Manzo white paper

Scan taken without patient attending the practice 

Scanbox 

Formulate STL file and fit aligner in surgery

80% repeatability from 2 scans

44.7% repeatability and reproducibility 

Discrepancy between scanbox and intra-oral scan varied between 0.5-1.9mm, angular measurements maximum error 8.9 degrees

2-3 appointments less

No difference in overall duration

Some people struggle to use

Accuracy and repeatability variable

No difference in the quality of the outcome

Unknown accuracy of occlusal assessments from a reliable retruded contact position

Patient motivation maybe better delivered in person

Ai environment cost 2-3% of energy used by data centres

Diagnostic and treatment planning acumen

Identify main aspect of malocclusion and address through efficient mechanics