Young-onset Colorectal Cancer Screening Based on Artificial Intelligence

Status Completed

Clinical Trial Summary

In this study, we aimed to develop, internally and temporally validate the machine learning models to help screen YOCRC bansed on the retrospective extracted Electronic Medical Records (EMR) data.

Clinical Trial Description

Diagnosis of young-onset colorectal cancer (YOCRC) has become more common in recent decades. Screening CRC among younger adults still remains a challenge. In this study, We plan to retrospectively extracte the relevant clinical data of young individuals who underwent colonoscopy from 2013 to 2022 using Electronic Medical Record (EMR). Multiple supervised machine learning techniques will be applied to distinguish YOCRC and non-YOCRC individuals, the above classifiers will be trained and internally validated in the training dataset and internal validation dataset admitted between 2013 and 2021, respectively. We will also assess the temporal external validity of the classifiers based on the admissions from 2022. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details

NCT number	NCT06342622
Study type	Observational
Source	Renmin Hospital of Wuhan University
Contact
Status	Completed
Phase
Start date	December 1, 2023
Completion date	January 25, 2024

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