Skip to content

A Prospective Cross-Sectional Study of an AI-Powered Tool for Automated Generation of Dental Electronic Medical Records

A Prospective Cross-Sectional Study of an AI-Powered Tool for Automated Generation of Dental Electronic Medical Records

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600116116
Enrollment
Unknown
Registered
2026-01-06
Start date
2025-08-20
Completion date
Unknown
Last updated
2026-01-12

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

Conditions

None

Interventions

There was no intervention in this study, so no grouping was made:There was no intervention in this study

Sponsors

Hospital of Stomatology, Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1: Over 18 years old, gender not limited. 2: Patients requiring dental treatment, either scheduled for or actively receiving care at our institution; 3: The patient or their legal guardian has provided informed consent and demonstrates willingness to comply with the treatment regimen.

Exclusion criteria

Exclusion criteria: 1: Comprehensive evaluation indicating contraindications to dental treatment; 2: Other circumstances deemed ineligible by the investigator.

Design outcomes

Primary

MeasureTime frame
Electronic Medical Record (EMR) Quality(AccuracyRecallEMR Quality ScoreFrequency of EMR Revisions);

Secondary

MeasureTime frame
EMR Deficiencies(Deficiency CategoriesSpecific Deficiency Descriptions);Clinical efficiency (EMR generation time, EMR revision time, physician satisfaction scores with the tool, etc.);

Countries

China

Contacts

Public ContactZetao Chen

Hospital of Stomatology, Sun Yat-sen University

chenzet3@mail.sysu.edu.cn+86 136 3246 9150

Outcome results

None listed

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