Renmin Hospital of Wuhan University
Wuhan, Hubei, China
Location status: Recruiting
NCT Number: NCT07073430
This study is a prospective,multi-center and observational clinical study.Investigators would like to innovatively construct a "trinity" database of colorectal tubular adenomas based on white light - magnifying chromo - pathological images.It simulates the decision - making logic of doctors, and based on the multimodal endoscopic LAFEQ method previously proposed, develop a multimodal deep - learning diagnostic model for colon adenomas and an interpretable risk prediction model for intestinal adenomas. While achieving high - precision auxiliary treatment decisions, clearly present the decision - making basis, and break through the limitation of poor interpretability of previous medical imaging AI models.
Interested in participating?
Request Info18 year and older
All sexes
Observational
Wuhan, Hubei, China
Location status: Recruiting
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
AI models for detecting intestinal adenoma in magnifying endoscopy with NBI.
Time frame: during endoscopy
The prediction rate of the interpretable artificial intelligence-assisted diagnosis model for the disease risk level.
Time frame: during endoscopy
The prediction rate of the interpretable artificial intelligence-assisted diagnosis model for the disease risk level.
Contact information is provided by the study sponsor or research team.
Renmin Hospital of Wuhan University
Other
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