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Study to compare computer based prediction and orthodontist decision in deciding whether teeth need removal for braces treatment

Predictive performance of artificial intelligence based deep learning automated model in orthodontic treatment decision: A retrospective study - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2026/04/109024
Enrollment
70
Registered
2026-04-21
Start date
Unknown
Completion date
Unknown
Last updated
2026-04-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: K088- Other specified disorders of teethand supporting structures

Interventions

Intervention1: Nil: Nil

Sponsors

Institute of Dental Sciences
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Angle s Class I or Angle s Class II malocclusion Permanent dentition

Exclusion criteria

Exclusion criteria: Angle s Class III malocclusion Orthognathic surgical treatment Craniofacial syndromes, congenital anomalies, or cleft lip and palate Mixed dentition or incomplete permanent dentition Severe dental anomalies such as supernumerary teeth, extensive hypodontia or significant tooth morphology abnormalities that may influence treatment planning

Design outcomes

Primary

MeasureTime frame
Accuracy of AI based deep learning model in predicting extraction versus non-extraction orthodontic treatment decisions compared to conventional diagnosisTimepoint: At baseline single time assessment using collected diagnostic records—

Secondary

MeasureTime frame
senstivity and specificitty of the AI model in treatment decision predictionTimepoint: At the time of data analysis—

Countries

India

Contacts

Public ContactAnkur gupta

Institute of Dental Sciences

swabhikhanagwal@gmail.com9910780294

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: May 1, 2026