The aim of this study is to investigate if the use of artificial intelligence (AI) in colonoscopy improves the polyp detection rate, and if the use of AI has a learning effect.
The endoscopists will use GI Genius from Medtronic, a device that uses artificial intelligence (AI) based on machine learning to detect polyps in the colon in real time during colonoscopy. The device interprets the endoscopy pictures and superimposes possible polyps with frames. The patients will be included in regular outpatient clinics in Western Norway. The endoscopists will be divided into groups depending on their experience. The endoscopists will perform colonoscopies in three phases; (1) before the use of AI, (2) during the use of AI and (3) after the use of AI. The investigators will then evaluate the polyp detection rate (PDR) in the three phases to see if AI increases PDR, and if there is a learning effect on PDR after the use of AI. The investigators will also evaluate if there is a difference in the learning-effect from AI-use depending on if the endoscopist is experienced or inexperienced. The PDR's are registered as part of Norway's national quality register of colonoscopy, Gastronet. The data registered in Gastronet can also help the investigators evaluate other outcomes such as withdrawal time, bowel preparation, patient reported pain, patient satisfaction and complications.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
5,034
The use of artificial intelligence during colonoscopy to improve polyp detection.
Standard colonoscopy.
Haraldsplass Deaconess Hospital
Bergen, Vestland, Norway
Haukeland University Hospital
Bergen, Vestland, Norway
Kanalspesialistene AS
Bergen, Vestland, Norway
Polyp detection rate (PDR) with and without artificial intelligence (AI)
Evaluate the PDR with and without the use of GI Genus artificial intelligence
Time frame: 18 months
PDR after the use of AI, is there a learning effect?
Evaluate if there is an improved PDR after the use of AI
Time frame: 18 months
Withdrawal time
To evaluate if the withdrawal time is influenced by the use of artificial intelligence
Time frame: 18 months
Complications
To evaluate if there are more registered complications with the use of AI
Time frame: 24 months
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