Diagnostic yield Evaluation Studies of a real-time endoscopic Image diagNosis support system using Artificial Intelligence technology

Diagnostic yield Evaluation Studies of a real-time endoscopic Image diagNosis support system using Artificial Intelligence technology - DESIGN AI-02 Pilot Study

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000041823

Enrollment

100

Registered

2020-09-25

Start date

2020-11-10

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

Colorectal Neoplasms

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: 1) Patients who undergo colonoscopy 2) Age: 20 to 90 (at the registry) 3) ECOG performance status: 0-2 4) No prior chemotherapy and radiation therapy for colorectal cancer 5) Patients who can follow Guidelines for gastroenterological endoscopy in patients undergoing antithrombotic treatment 6) Written informed consent

Exclusion criteria

Exclusion criteria: 1) Familial adenomatous polyposis 2) Patients with complications, such as chronical hematological disease 3) Patients with active inflammatory bowel diseases, such as ulcerative colitis or Crohn's disease

Design outcomes

Primary

Measure	Time frame
Adenoma Detection Rate	—

Secondary

Measure	Time frame
1) Adenoma per Positive Colonoscopy 2) Polyp Detection Rate 3) Total procedure time 4) Insertion time 5) Withdrawal time 6) Acceptance (Questionnaire) 7) Sessile serrated lesion detection rate 8) Flat adenoma Detection Rate 9) Depressed lesion Detection Rate	—

Countries

Japan

Contacts

Public ContactMasayoshi Yamada

National Cancer Center Hospital Endoscopy Division

masyamad@ncc.go.jp03-3542-2511

Outcome results