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Diagnostic Efficiency and Impact on Physicians' Learning Process of an Artificial Intelligence Ultrasound Diagnosis System for Thyroid Nodules:A Multicentre Randomized Controlled Trial

Diagnostic Efficiency and Impact on Physicians' Learning Process of an Artificial Intelligence Ultrasound Diagnosis System for Thyroid Nodules:A Multicentre Randomized Controlled Trial

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR1900024194
Enrollment
Unknown
Registered
2019-06-29
Start date
2019-07-01
Completion date
Unknown
Last updated
2019-07-01

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

Conditions

Thyroid nodules

Interventions

intelligence&#32
Gold Standard:physicians' diagnose
Index test:artificial&#32

Sponsors

The Second Affiliated Hospital of Fujian Medical University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: (1) The number of thyroid nodules =4 in the same case; (2) The maximum diameter of the nodules =0.3cm; (3) Standard cross section and longitudinal section images were saved during the ultrasonic examination; (4) Images without obvious artificial marks and measuring marks (measuring points and lines can cause misjudgment of software).

Exclusion criteria

Exclusion criteria: (1) Thyroid nodule patients who were examined not the first time; (2) Ultrasound images were not clear, or nodules are too large to be fully displayed in a single ultrasound image; (3) US-FNA pathological results were uncertain; (4) Failed to obtain pathological results.

Design outcomes

Primary

MeasureTime frame
Diagnostic accuracy of physician;Diagnostic accuracy of artificial intelligence;

Secondary

MeasureTime frame
Diagnostic sensitivity of physician;Diagnostic sensitivity of artificial intelligence;Diagnostic specificity of physician;Diagnostic specificity of artificial intelligence;The time required for the diagnosis;

Countries

China

Contacts

Public ContactQichen Su

The Second Affiliated Hospital of Fujian Medical University

sqc0595@163.com+86 13559575368

Outcome results

None listed

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