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Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma
Sponsor: The First Affiliated Hospital of Anhui Medical University
Summary
This study aims to develop a predictive model using deep learning and radiomics to assess the likelihood of lymph node metastasis in patients with early-stage esophageal squamous cell carcinoma (ESCC). Lymph node metastasis is a critical factor in determining the treatment approach and prognosis for ESCC patients. By analyzing medical imaging data, we hope to create a non-invasive method that can assist doctors in making more accurate treatment decisions. This research could improve patient outcomes by enabling earlier and more tailored interventions.
Official title: Deep Learning and Radiomics for Prediction of Lymph Node Metastasis in Early-stage Esophageal Squamous Cell Carcinoma
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
500
Start Date
2024-05-01
Completion Date
2025-11-30
Last Updated
2025-07-03
Healthy Volunteers
No
Conditions
Interventions
The prediction model of lymph node metastasis in early esophageal squamous cell carcinoma
The predictive performance of the model was validated in the test set. The optimal prediction model was determined based on the AUC and ACC. To assess the robustness of the chosen model, ROC analysis was conducted on the external validation set.
Locations (1)
The First Affiliated Hospital of Anhui Medical University
Hefei, Anhui, China