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NCT04071678
A Randomized Controlled Multicenter Study of Artificial Intelligence Assisted Digestive Endoscopy
trial testing Careful examination during endoscopic procedures to identify lesions in Artificial Intelligence in 3,600 participants. Status unknown.
1 August 2021
Quick facts
| Lead sponsor | Second Affiliated Hospital, School of Medicine, Zhejiang University |
|---|---|
| Status | Status unknown |
| Study type | OBSERVATIONAL |
| Enrollment | 3,600 |
| Start date | 1 August 2019 |
| Primary completion | 1 August 2021 |
| Estimated completion | 30 December 2021 |
| Sites | 1 location across China |
Drugs / interventions tested
- Careful examination during endoscopic procedures to identify lesions
Conditions studied
- Artificial Intelligence — all drugs for Artificial Intelligence →
Sponsor
Second Affiliated Hospital, School of Medicine, Zhejiang University
Who can join
18 and older, any sex, with Artificial Intelligence. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
Digestive endoscopy center of the second affiliated hospital of medical college of zhejiang university and engineers of naki medical co., ltd. in Hong Kong independently developed an ai-assisted diagnostic model of digestive endoscopy in the early stage, namely the deep learning model.The deep learning model through the early stage of the study, is able to identify lesions of digest tract.The sensitivity for the diagnosis of some diseases, such as colon polyps, is 99%. On the one hand, this auxiliary diagnostic model can guide endoscopic examination for beginners; on the other hand, it can improve the detection rate of lesions and reduce the rate of missed diagnosis; on the other hand, the overall operating efficiency of the endoscopic center is improved, which is conducive to the quality control of endoscopic examination. Now the AI-assisted diagnostic model has been further improved, and it is planned to carry out further clinical verification in the digestive endoscopy center of our hospital. It is connected to the endoscopic system of our hospital and used simultaneously with the existing image-text system of endoscopy to compare the practicability, sensitivity and specificity of AI-assisted diagnosis model in the diagnosis of digestive tract diseases, and focus on the quality control of endoscopic examination.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
- PubMed search for NCT04071678
- Europe PMC full search
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT04071678 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Second Affiliated Hospital, School of Medicine, Zhejiang University
- Last refreshed: 22 October 2019
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT04071678.
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