NCT04957407

The Research of Constructing a Risk Assessment Model for Gastric Cancer Based on Machine Learning

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 5,000 (estimated)
• Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University · Academic / Other
• Sex: All
• Age: 25 Years – 75 Years
• Healthy volunteers: Not accepted

Summary

Based on the gastric cancer database established earlier, this project explored the PG standard suitable for Chinese people, and further explored the establishment of machine learning model to stratify gastric cancer risk in the population, guide the frequency of gastroscopy screening, and extract important gastric cancer risk factors from it.Establish electronic health records of gastric organs, track the development and outcome of gastric diseases through deep learning method, in order to predict the development and outcome of gastric diseases;Then, the simulation hypothesis deductive method is used to compare the outcomes that may be caused by different lifestyles with the help of deep learning model, so as to guide patients to develop a better lifestyle and explore the establishment of health management paths for gastric cancer patients and high-risk groups in China.

Conditions

• Gastric Cancer
• Precancerous Lesion
• Mechine Learning

Interventions

Type	Name	Description
OTHER	pepsinogen	diagnostic value of pepsinogen for severe atrophy and gastric cancer

Timeline

• Start date: 2019-01-01
• Primary completion: 2022-05-31
• Completion: 2022-12-31
• First posted: 2021-07-12
• Last updated: 2021-07-12

Locations

2 sites across 1 country: China