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Evaluating space maintenance needs by comparing deep learning and traditional analysis methods a pilot study

Assessing the need for space maintenance- deep learning system vs conventional space analysis- a pilot study - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/09/095331
Enrollment
385
Registered
2025-09-24
Start date
Unknown
Completion date
Unknown
Last updated
2025-10-13

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

Conditions

None listed

Interventions

Intervention1: Nil: Nil

Sponsors

SRM Kattankulathur Dental College
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Children with mixed dentition between 6-11 years of age

Exclusion criteria

Exclusion criteria: Children with any systemic diseases Children with cleft lip/palate or other craniofacial anomalies Children with dental anomalies Children with full coverage restorations Patients with oral sensorimotor discomfort Children with limited mouth opening

Design outcomes

Primary

MeasureTime frame
Prediction of mesio-distal width of unerupted canine and premolars using deep learning system Timepoint: Time point 1- 1month (impression making) Time point 2- 2month (impression making) Time point 3- 3month (impression making) Time point 4- 4month (impression making) Time point 5- 5month (impression making) Time point 6- 6month (impression making)—

Secondary

MeasureTime frame
NILTimepoint: NIL—

Countries

India

Contacts

Public ContactArya binu

SRM Kattankulathur Dental College

ab7622@srmist.edu.in8156870997

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026