Clinical trial · Observational
Application of Artificial Intelligence for Early Diagnosis of Gastric Cancer During Optical Enhancement Magnifying Endoscopy
NCT04563416CI-TRIAL-00047298unknownClinicalTrials.gov clinicaltrialsProvenance
- 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)
Previous prospective randomized controlled study demonstrated higher accuracy rate of diagnosing early gastric cancers by Magnifying image-enhanced endoscopy than conventional white-light endoscopy. Nevertheless, it is difficult to differentiate early gastric cancer from noncancerous lesions for beginner. we developed a new computer-aided system to assist endoscopists in identifying early gastric cancers in magnifying optical enhancement images.
Conditions
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Artificial Intelligence | — | UNRESOLVED | — |
| Magnifying Endoscopy | — | UNRESOLVED | — |
| Optical Enhancement Endoscopy | — | UNRESOLVED | — |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (1)
- label
- Patients who need undergo magnifying endoscopy
Primary outcomes (1)
- measure
- the diagnosis efficiency of the computer-assist diagnosis tool
- timeFrame
- 12 months
- description
- the sensitivity, specificity and accuracy of the computer-assist diagnosis tool
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * patients receive optical magnifying OE endoscopy examination Exclusion Criteria: * Patients with advanced cancer, lymphoma,active stage of ulcer and artificial ulcer after ESD were excluded.
References
Publications (1)
- DERIVEDMa M, Li Z, Yu T, Liu G, Ji R, Li G, Guo Z, Wang L, Qi Q, Yang X, Qu J, Wang X, Zuo X, Ren H, Li Y. Application of deep learning in the real-time diagnosis of gastric lesion based on magnifying optical enhancement videos. Front Oncol. 2022 Aug 5;12:945904. doi: 10.3389/fonc.2022.945904. eCollection 2022. PMID 35992850