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A Deep Neural Network Improves the Quality of Endoscopic Examination

A Deep Neural Network Improves the Quality of Endoscopic Examination

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR1800014809
Enrollment
Unknown
Registered
2018-02-07
Start date
2018-08-01
Completion date
Unknown
Last updated
2020-01-06

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

Conditions

Gastric cancer

Interventions

analysis&#32
artificial&#32
intelligence&#32
Gold Standard:Consensus from endoscopists
Index test:Endoscopic&#32
image&#32
collection&#32
of&#32
gastric&#32
cancer&#32
and&#32

Sponsors

Renmin Hospital of Wuhan University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 81 Years

Inclusion criteria

Inclusion criteria: 1. Patiens aged 18 years or older undergoing gastroscopy. 2. Be able to read, understand and sign informed consent. 3. ASA (American Society of Anesthesiology) risk class 1, 2 or 3

Exclusion criteria

Exclusion criteria: 1. Patients with absolute contraindications to EGD examination; 2. Patients in pregnancy; 3. A history of previous gastric surgery; 4. Allergic to anaesthetic in previous medical history; 5. The researchers believe that the patient is not suitable to participate in the trial.

Design outcomes

Primary

MeasureTime frame
Blind sopt rate;—

Secondary

MeasureTime frame
The rate of blind spots in patients' photodocumentationation;Completeness of photodocumentation generated by endoscopists;Completeness of photodocumentation generated by AI in AI group;Completeness of photodocumentation generated by AI and endoscopists in AI group;—

Countries

China

Contacts

Public ContactYu Honggang
yuhonggang1968@163.com+86 13871281899

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 21, 2026