Clinical trial · Observational
Multimodal Model Predicts Recurrence
Multimodal Clinical-imaging-pathology-driven Artificial Intelligence Model for Predicting Postoperative Recurrence of Locally Advanced Gastric Cancer
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Gastric Adenocarcinoma | Gastric Adenocarcinoma | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Multimodal AI-driven predictive model | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- Prediction accuracy of postoperative recurrence in locally advanced gastric cancer
- timeFrame
- 24 months postoperative follow-up
- description
- The primary outcome measure is the accuracy of the multimodal AI model in predicting the risk of postoperative recurrence in patients with locally advanced gastric cancer. This is assessed by comparing the model's predictions with actual recurrence events over a specified follow-up period, allowing evaluation of its effectiveness in identifying high-risk patients and guiding clinical decisions.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 75 Years
Show eligibility criteria text
\*\*Inclusion Criteria:\*\* * Patients diagnosed with locally advanced gastric cancer (Stage II or III). * Patients who have undergone surgical resection for gastric cancer. * Patients with complete clinical, imaging, and pathology data available for analysis. * Age 18 years or older. * Patients who provide informed consent to participate in the study. \*\*Exclusion Criteria:\*\* * Patients with distant metastasis (Stage IV) at the time of diagnosis. * Patients with incomplete or missing clinical, imaging, or pathology data. * Patients who have received prior treatment for gastric cancer other than surgical resection. * Patients with other concurrent malignancies. * Patients who are unable or unwilling to comply with the study follow-up requirements.
References
Publications (0)
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