Development of an artificial intelligence system using deep learning to indicate anatomical landmarks during laparoscopic gastrectomy

Development of an artificial intelligence system using deep learning to indicate anatomical landmarks during laparoscopic gastrectomy - Development of an artificial intelligence system using deep learning to indicate anatomical landmarks during laparoscopic gastrectomy

Status

Active, not recruiting

Phases

Phase 1

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000042569

Enrollment

Registered

2020-11-26

Start date

2020-12-01

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

gastric cancer

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: 1) Histologically proven gastric carcinoma. 2) Clinical Stage I to III gastric carcinoma according to the Japanese classification system. 3) Regardless of occupation and number of tumors. 4) Aged 20 to 85 years old. 6) PS (ECOG) 0 or 1. 7) Sufficient organ function. 8) Provided written informed consent.

Exclusion criteria

Exclusion criteria: 1) Severe mental disease. 2) Continuous systemic steroid therapy. 3) History of myocardial infarction or unstable angina pectoris within 6 months. 4) Uncontrollable hypertension. 5) Uncontrollable diabetes mellitus or administration of insulin. 6) Severe respiratory disease requiring continuous oxygen therapy.

Design outcomes

Primary

Measure	Time frame
Accuracy of landmark detection	—

Secondary

Measure	Time frame
Operative time Amount of blood loss Conversion ratio to conventional surgery Morbidity Mortality	—

Countries

Japan

Contacts

Public ContactKosuke Suzuki

Oita University Faculty of Medicine Gastroenterological and Pediatric Surgery

kosuzuki@oita-u.ac.jp097-586-5843

Outcome results