AI-Driven Cancer Diagnosis and Prediction With EHR
Recruiting now
Conditions studied: Tumor
In brief
This is a multi-center, clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for identifying and diagnosing cancer, leveraging multimodal health data.
Key facts
- Study ID
- NCT06791473
- Run by
- The Eye Hospital of Wenzhou Medical University
- People needed
- 1000000
- Starts
- 2025-01-19
- Expected to finish
- 2025-10-01
- Last updated by the study team
- 2025-07-30
Who can join
Age: any, up to 90. Sex: any. Healthy volunteers: accepted.
You may qualify if…
- 1、Patients with comprehensive electronic health records (EHRs), including medical history, laboratory test results, imaging data, and genetic data (if available).
- Individuals without severe cognitive impairments or conditions that would prevent them from providing informed consent or participating in the study.
- Parents or guardians must provide informed consent for minors, while adult participants must provide informed consent for themselves.
You may not qualify if…
- Patients with incomplete or missing key electronic health record data or insufficient follow-up data.
- Individuals with severe cognitive disorders or other terminal illnesses that would prevent meaningful participation.
- Pregnant women (although pediatric cancers are being considered, pregnant women would be excluded for safety reasons).
Where it is running
- Guangzhou Women and Children's Medical Center — Guangzhou, Guangdong, China (enrolling)
- Nanfang Hospital — Guangzhou, Guangdong, China (enrolling)
- Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University — Guangzhou, Guangdong, China (enrolling)
- Sun Yat-sen University Cancer Hospital — Guangzhou, Guangdong, China (enrolling)
- West China Hospital — Chengdu, Sichuan, China (enrolling)
- First Affiliated Hospital of Wenzhou Medical University — Wenzhou, Zhejiang, China (enrolling)
- Second Affiliated Hospital of Wenzhou Medical University — Wenzhou, Zhejiang, China (enrolling)
Full record on ClinicalTrials.gov
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