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Multimodal Model Predicts Recurrence (FUTURE12)
This study focuses on developing an advanced model that combines clinical information, imaging, and pathology data to predict the likelihood of cancer returning after surgery in patients with locally advanced gastric cancer. By using artificial intelligence (AI), this model analyzes various data sources to create a more accurate prediction of recurrence risk, which can help doctors, patients, and families better understand the chances of recurrence. This AI-driven approach allows healthcare providers to make more informed decisions about personalized follow-up care and potential additional treatments to improve patient outcomes.
Details
| Lead sponsor | Qun Zhao |
|---|---|
| Status | COMPLETED |
| Enrolment | 93 |
| Start date | Sat Jan 01 2022 00:00:00 GMT+0000 (Coordinated Universal Time) |
| Completion | Thu Oct 31 2024 00:00:00 GMT+0000 (Coordinated Universal Time) |
Conditions
- Gastric Adenocarcinoma
Interventions
- Multimodal AI-driven predictive model
Countries
China