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NCT04079478: AID
The AID Study: Artificial Intelligence for Colorectal Adenoma Detection
trial testing AI in Colon Cancer in 700 participants. Completed in 31 December 2019.
31 December 2019
Quick facts
| Lead sponsor | Istituto Clinico Humanitas |
|---|---|
| Status | Completed |
| Study type | OBSERVATIONAL |
| Enrollment | 700 |
| Start date | 25 September 2019 |
| Primary completion | 31 December 2019 |
| Estimated completion | 31 December 2019 |
| Sites | 1 location across Italy |
Drugs / interventions tested
- AI — full drug profile →
Conditions studied
- Colon Cancer — all drugs for Colon Cancer →
Sponsor
Istituto Clinico Humanitas
Who can join
Adults 40 to 80, any sex, with Colon Cancer. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
Colonoscopy is clinically used as the gold standard for detection of colon cancer (CRC) and removal of adenomatous polyps. Despite the success of colonoscopy in reducing cancer-related deaths, there exists a disappointing level of adenomas missed at colonoscopy. "Back-to-back" colonoscopies have indicated significant miss rates of 27% for small adenomas (\< 5 mm) and 6% for adenomas of more than 10 mm in diameter. Studies performing both CT colonography and colonoscopy estimate that the colonoscopy miss rate for polyps over 10 mm in size may be as high as 12%. The clinical importance of missed lesions should be emphasized because these lesions may ultimately progress to CRC8. Limitations in human visual perception and other human biases such as fatigue, distraction, level of alertness during examination increases such recognition errors and way of mitigating them may be the key to improve polyp detection and further reduction in mortality from CRC. In the past years, a number of CAD systems for detection of polyps from endoscopy images have been described. However, the benefits of traditional CAD technologies in colonoscopy appear to be contradictory, therefore they should be improved to be ultimately considered useful. Recent advances in artificial intelligence (AI), deep learning (DL), and computer vision have shown potential to assist polyp detection during colonoscopy.
Publications & conference data
No peer-reviewed publications indexed yet for this trial. Completed trials usually publish results within 12-18 months.
Verify or expand the search:
- PubMed search for NCT04079478
- Europe PMC full search
- ASCO Meeting Library
- ESMO Meeting Library
- bioRxiv preprints
- medRxiv preprints
- Google Scholar
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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 NCT04079478 (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 Istituto Clinico Humanitas
- Last refreshed: 12 February 2020
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/NCT04079478.
Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing