Clinical usefulness of artificial intelligence for the diagnosis using magnifying endoscopy with narrow-band imaging

Clinical usefulness of artificial intelligence for the diagnosis using magnifying endoscopy with narrow-band imaging - AI for M-NBI

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000050543

Enrollment

100

Registered

2023-03-09

Start date

2023-04-01

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

Early gastric cancer

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Endoscopic images which were captured and recorded using magnifying endoscopy with narrow-band imaging in Fukuoka University Chikushi Hospital

Exclusion criteria

Exclusion criteria: Endoscopic images whose quality is not enough for the analysis

Design outcomes

Primary

Measure	Time frame
Specificity for the diagnosis of early gastric cancer by artificial intelligence	—

Secondary

Measure	Time frame
Sensitivity, accuracy, positive predictive value, negative predictive value and AUC for the diagnosis of early gastric cancer by artificial intelligence	—

Countries

Japan

Contacts

Public ContactKenshi Yao

Fukuoka University Chikushi Hospital Department of Endoscopy

yao@fukuoka-u.ac.jp092-921-1011

Outcome results