Skip to content

The one-stop decision-making system based on convolution neural network on preoperative diagnosis of early gastric cancer

Research on one-stop intelligent decision-making system before endoscopic resection of early gastric cancer based on big data analysis and convolutional neural network

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000035640
Enrollment
Unknown
Registered
2020-08-15
Start date
2020-08-31
Completion date
Unknown
Last updated
2020-11-24

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

Conditions

gastric cancer

Interventions

Gold Standard:Pathological diagnosis of patients with gastric cancer after operation is performed by pathologists.
intelligent&#32
system&#32
of&#32
early&#32
cancer&#32
based&#32
on&#32
data&#32
analysis&#32
and&#32
neural&#32

Sponsors

Zhongshan Hospital, Fudan University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
15 Years to 90 Years

Inclusion criteria

Inclusion criteria: (1) Aged 15-90 years old; (2) Gastroscopy is acceptable; (3) All patients have complete pathological diagnosis information.

Exclusion criteria

Exclusion criteria: (1) There is bleeding around the lesion due to endoscopic operation; (2) There is a history of other primary tumors; (3) Poor gastric inflation or poor image quality due to technical reasons; (4) The pathological diagnosis of the lesions is controversial; (5) there is a large amount of food or fluid retention in the stomach, which leads to unclear observation of the lesion; (6) Poor quality of pathological section.

Design outcomes

Primary

MeasureTime frame
invasion depth;SEN, SPE, ACC, AUC of ROC, NLR, PLR, etc.;Consistency;

Countries

China

Contacts

Public ContactLi Quanlin

Zhongshan Hospital, Fudan University

li.quanlin@zs-hospital.sh.cn+86 13564671882

Outcome results

None listed

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