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Research on Artificial Intelligence-based Risk Stratification Prediction, Automatic Detection and Prediction of Lymph Node Metastases in Thyroid Cancer

Research on Artificial Intelligence-based Risk Stratification Prediction, Automatic Detection and Prediction of Lymph Node Metastases in Thyroid Cancer

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600125951
Enrollment
Unknown
Registered
2026-06-01
Start date
2026-06-01
Completion date
Unknown
Last updated
2026-06-08

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

Conditions

Thyroid Cancer

Interventions

Gold Standard:Pathological examination confirmed papillary thyroid carcinoma.
Index test:This study constructs a deep learning model based on pathological images of thyroid papillary carcinoma to achieve precise risk stratification of thyroid cancer and automatic detection and

Sponsors

Ganzhou Municipal Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 90 Years

Inclusion criteria

Inclusion criteria: 1.Patients with papillary thyroid carcinoma who underwent surgical resection combined with cervical lymph node dissection. 2.The final pathological diagnosis was confirmed as papillary thyroid carcinoma. 3.Valid pathological slides are available for acquisition. 4.Complete clinical data are accessible, with no restrictions on age or gender.

Exclusion criteria

Exclusion criteria: 1.Patients with papillary thyroid carcinoma who did not undergo cervical lymph node dissection. 2.Pathological slide images with severe fading.

Design outcomes

Primary

MeasureTime frame
Accuracy;Sensitivity;Specificity;Positive predictive value ;Negative Predictive Value;

Countries

China

Contacts

Public ContactFang Weilan

Ganzhou Municipal Hospital

fangweilan715@163.com+86 797 820 8510

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jun 11, 2026