The effect of artificial intelligence-assisted early gastric cancer detection model on the detection rate of early gastric cancer: a multicenter randomized controlled study

Status

Recruiting

Phases

Early Phase 1

Study type

Interventional

Source

ChiCTR

Registry ID

ChiCTR2100050667

Enrollment

Unknown

Registered

2021-09-01

Start date

2021-10-01

Completion date

Unknown

Last updated

2022-05-02

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

Conditions

Early gastric cancer

Interventions

Experimental group1:White light gastroscope + AI system assistance

Experimental group2:AI system assistance + white light gastroscope

Eligibility

Sex/Gender

Male

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age 18 years or older, regardless of gender; 2. A history of endoscopic resection of early gastric cancer or precancerous lesions; 3. Agree and be able to sign an informed consent.

Exclusion criteria

Exclusion criteria: 1. History of gastric resection or reconstruction; 2. Complete pyloric obstruction; 3. Active upper gastrointestinal bleeding; 4. Abnormal coagulation function; 5. Severe heart, liver and kidney insufficiency; 6. Pregnant and lactating women; 7. Mental illness and severe neurosis; 8. Participated in other clinical studies within 1 month.

Design outcomes

Secondary

Measure	Time frame
Detection rate of early gastric cancer and precancerous lesions in different age subgroups;Gastroscopy time;	—

Primary

Measure	Time frame
Detection rate of early gastric cancer and precancerous lesions;	—

Countries

China

Contacts

Public ContactXu Guifang

The Affiliated Drum Tower Hospital of Nanjing University Medical School

xuguifang@njglyy.com+86 13852293376

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026