Ignite Creation Date:
2024-05-06 @ 8:20 PM
Last Modification Date:
2024-10-26 @ 3:25 PM
Study NCT ID:
NCT06342622
Status:
COMPLETED
Last Update Posted:
2024-04-02
First Post:
2024-03-15
Brief Title:
Young-onset Colorectal Cancer Screening Based on Artificial Intelligence
Sponsor:
Renmin Hospital of Wuhan University
Organization:
Renmin Hospital of Wuhan University
Study Overview
Official Title:
Application of Artificial Intelligence for Young-onset Colorectal Cancer Screening Based on Electronic Medical Records
Status:
COMPLETED
Status Verified Date:
2024-01
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief 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
Detailed 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 Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None