USAGE OF ARITIFICIAL INTELLIGENCE IN AIDING WITH COLONIC SESSILE SERRATED LESIONS DETECTION AND DIAGNOSIS (AI-SSL)

ConditionsSessile Serrated Lesion CADe

Trial statusRecruiting

Trial phaseNot applicable

Trial typeInterventional

Biological sexAll

Age40-80

SponsorNational Healthcare Group, Singapore

About this trial

The aim of this study is to is to evaluate if a real-time Computer Aided Detection (CADe) system can help improve the detection of SSL(sessile serrated lesions) versus a conventional colonoscopy (CC) using white light examination(WLE).

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

None

Disqualifiers

None

Trial design

Design model

Parallel

Treatments tested in this trial

usage of CADe system
Device
A real-time Computer Aided Detection (CADe) system can help improve the detection of SSL versus a conventional colonoscopy (CC) using white light examination(WLE).

Treatment groups

628 Participants

are divided into 2 treatment groups

Group A: AI-assisted colonoscopyActive comparator 1 intervention

Group B: Conventional ColonoscopyNo intervention 0 interventions

Trial outcomes

Primary outcomes

SSL per colonoscopy (SPC) using White Light Endoscopy alone vs enhancement by CADe system.

Time frame

up to a year

Secondary outcomes

1) Adenoma per colonoscopy (APC) using White Light Endoscopy alone vs enhancement by CADe system. 2) Polyp per colonoscopy (PPC) using White Light Endoscopy alone vs enhancement by CADe system. 3) Difference in the SPC, APC, PPC for each proceduralist

Time frame

up to a year

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

National Healthcare Group, Singapore

Lead sponsor

Changi General Hospital

Collaborator

National University Health System, Singapore