MedTrace Logo

Multi-center and Multi-modal Deep Learning Study of Gastric Cancer

NCT05001321 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 3300

Last updated 2021-08-11

No results posted yet for this study

Summary

To assist postoperative pathological diagnosis and classification of gastric cancer by machine learning; To improve the accuracy of pathological diagnosis of gastric cancer by machine learning; To predict the effectiveness of treatment for gastric cancer by deep learning; To construct a model to predict the survival of gastric cancer patients by multimodal deep learning.

Conditions

  • Stomach Neoplasms

Interventions

RADIATION

The whole abdomen contrast-enhanced CT scan

All the participants were measured by the whole abdomen contrast-enhanced CT scan.

OTHER

H&E stained sections and slides

HE pathological examination was performed on all specimens of enrolled patients.

Sponsors & Collaborators

  • The Second Hospital of Shandong University

    collaborator OTHER

  • Chaoyang Central Hospital

    collaborator OTHER

  • The General Hospital of Fushun Mining Bureau

    collaborator UNKNOWN

  • The fourth People's Hospital of Changzhou

    collaborator UNKNOWN

  • First Hospital of Jinzhou Medical University

    collaborator UNKNOWN

  • First Hospital of China Medical University

    lead OTHER

Principal Investigators

  • Kai Li, MD · First Hospital of China Medical University

Eligibility

Min Age
18 Years
Max Age
79 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-07-01
Primary Completion
2022-01-31
Completion
2024-12-31

Countries

  • China

Study Locations

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05001321 on ClinicalTrials.gov