NCT05001321

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

Multi-center and Multi-modal Deep Learning Study of Diagnosis, Therapeutic Outcome and Prognosis of Gastric Cancer

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 3,300 (actual)
• Sponsor: First Hospital of China Medical University · Academic / Other
• Sex: All
• Age: 18 Years – 79 Years
• Healthy volunteers: Not accepted

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

Type	Name	Description
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.

Timeline

• Start date: 2021-07-01
• Primary completion: 2022-01-31
• Completion: 2024-12-31
• First posted: 2021-08-11
• Last updated: 2021-08-11

Locations

6 sites across 1 country: China