Clinical trial · Interventional
Validation of Joint-AI in Diagnosing Pancreatic Solid Lesions
Validation of a Multimodal Artificial Intelligence Model in in Diagnosing Pancreatic Solid Lesions: a Prospective, Multicenter, Randomized, Controlled Trial
- 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 clinical trial aims to learn if a multimodal artificial intelligence (AI) model can enhance the diagnosis of pancreatic solid lesions. The main questions it aims to answer are: 1. Does the AI model enhance the diagnostic performance of endoscopists in diagnosing pancreatic solid lesions? 2. Does the addition of interpretability analysis further improve the diagnostic performance of the assisted endoscopists? Researchers will compare the diagnostic performance of endoscopists with or without the assistance of the AI model. Participants will: 1. Their clinical data will be prospectively collected. 2. They will be randomized to the AI-assist group and the conventional diagnosis group.
Conditions
Conditions (5)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Autoimmune Pancreatitis | — | UNRESOLVED | — |
| Pancreatic Cancer | Malignant Pancreatic Neoplasm | CURATED_EXACT | 0.92 |
| Pancreatic Neuroendocine Neoplasms (pNETs) | Primitive Neuroectodermal Tumor | ALIAS | 0.85 |
| Pancreatitis | — | UNRESOLVED | — |
| Solid Pseudopapillary Neoplasm of the Pancreas | Solid Pseudopapillary Neoplasm of the Pancreas | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (2)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| The assistance of the interpretable Joint-AI model | Diagnostic Test | — | UNRESOLVED |
| The assistance of the Joint-AI model | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (3)
- type
- NO_INTERVENTION
- label
- Conventional diagnosis
- description
- Endoscopists diagnose pancreatic solid lesions according to endoscopic ultrasound images and clinical data.
- type
- EXPERIMENTAL
- label
- Joint-AI assisted diagnosis
- description
- Endoscopists diagnose pancreatic solid lesions based on endoscopic ultrasound images, clinical data, and predictions made by the Joint-AI model.
- interventionNames
- Diagnostic Test: The assistance of the Joint-AI model
- type
- EXPERIMENTAL
- label
- Interpretable Joint-AI assisted diagnosis
- description
- Endoscopists diagnose pancreatic solid lesions based on endoscopic ultrasound images, clinical data, predictions given by the Joint-AI, and interpretability analysis results used to improve the transparency of the decision-making process of the Joint-AI model.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Imaging examinations (MRI, CT, B-ultrasound) show a solid mass in the pancreas, which requires endoscopic ultrasound guided-fine needle aspiration/biopsy (EUS-FNA/B) to clarify the nature of the lesion in patients. * Written consent provided Exclusion Criteria: * Age under 18 years old
References
Publications (0)
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