Velidation research of colonoscopy using artificial intelligence

Clinical performance of computer-aided detection of colorectal neoplasia using artificial intelligence

Status

Active, not recruiting

Phases

Unknown

Study type

Interventional

Source

JPRN

Registry ID

JPRN-jRCT1030220081

Enrollment

400

Registered

2022-05-28

Start date

2021-01-06

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Neoplastic polyp of the colon and rectum colorectal neoplasia

Interventions

We enrolled 415 subjects who under went colonoscopy at our institution from January 2021 to March 2022.The randomization method used in this study was the numbered container method according to the CO

D016449

Numbered container method

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Colorectal cancer screening endoscopy, colonoscopy after fecal occult blood positive test, surveillance after colorectal polyp resection

Exclusion criteria

Exclusion criteria: After colorectal surgery or inflammatory bowel disease

Design outcomes

Primary

Measure	Time frame
Adenoma detection rate in total colonoscopy	—

Secondary

Measure	Time frame
Adenoma miss rate in recto-sigmoid scopy	—

Contacts

Public ContactHirotaka Nakashima

Foundation for Detection of Early Gastric Carcinoma

nakashima@soiken.or.jp+81-3-3668-6803

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026