FindTrial
Sign In

To compare the Evaluation of Probe Transparency, Transgingival probing and Machine Learning Software Methods for the assessment of Gingival Thickness.

Comparative Evaluation of Probe Transparency, Transgingival probing and Machine Learning Software Methods for the assessment of Gingival Phenotype

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2022/08/044692
Enrollment
382
Registered
2022-08-16
Start date
Unknown
Completion date
Unknown
Last updated
2022-10-17

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

Conditions

None listed

Interventions

Intervention1: Machine Learning Software: Group III- Gingival phenotype assessment using Machine Learning Software Method. Control Intervention1: Probe Transparency: Group I- Gingival phenotype assess

Sponsors

Self
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: 1. Periodontally healthy individuals. 2. Presence of all anterior teeth in both upper and lower jaw.

Exclusion criteria

Exclusion criteria: 1. Pregnancy and lactation. 2. Gingival recession in the anterior teeth. 3. Presence of any systemic disease. 4. Extensive restorations. 5. Use of any medication possibly affecting the periodontal tissues. 6. Malposed teeth.

Design outcomes

Primary

MeasureTime frame
To evaluate the use of Probe Transparency, Transgingival probing and Machine Learning Software Methods for the assessment of Gingival Phenotype.Timepoint: At baseline—

Secondary

MeasureTime frame
To compare the use of Probe Transparency, Transgingival probing and Machine Learning Software Methods for the assessment of Gingival Phenotype.Timepoint: At baseline—

Countries

India

Contacts

Public ContactSupriya Kaule

VSPM Dental college and Research Centre

drsurekhar@gmail.com9011071477

Outcome results

None listed

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