Artificial Intelligence (AI)NCT07023471

Artificial Intelligence-assisted Colonoscopy, Tandem Study

A study testing Group A (Trainee --> expert), Group B (Trainee +AI --> expert) and Group C (Trainee --> expert + AI) in people with Artificial Intelligence (AI) and Colonoscopy Education, run by Mahidol University at 1 site in Thailand.

Enrolling by invitation

Enrolling by invitation. The study team selects and invites participants, usually from an existing group of patients.

Sites and contacts

Official record

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Trial summary

Who is it for?: Ages 40 to 85 years
Conditions the study is for: Artificial Intelligence (AI), Colonoscopy Education, Adenoma Colon Polyp
What is being tested?: Group A (Trainee --> expert), Group B (Trainee +AI --> expert) and Group C (Trainee --> expert + AI)
Type of treatment: Medical device
Could I receive a placebo?: Yes, some participants may receive a placebo
How many people: 364 participants
Where: 1 siteThailand
Study dates: 13 May 2025to 31 Dec 2026
Phase: Interventional
Are there results?: Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

Ages 40 to 85 years
All sexes
No healthy volunteers
Adult, Older adult

Who may be able to join

Age 40 - 85 years old
Appointment for colonoscopy for colorectal cancer screening

Who cannot join

Previous history of bowel obstruction or perforation
Presence of coagulopathy (Prothrombin time >, = 3 second ULN; Platelet < 50,000)
Previously diagnosed with inflammatory bowel disease or polyposis syndrome
Pregnancy or lactation
Severe comorbities or American Society of Anesthesiologist classification >, = 3
Unable to sign informed consent

Trial locations and contacts

1 site in 1 country. Contact the study team or a site near you to ask about taking part.

Thailand1 site

Division of Gastroenterology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
Bangkok, Bangkok

Other trials in Thailand

About this study

Official title: Effect of an Artificial Intelligence-assisted Colonoscopy on Adenoma Miss Rate of Trainee-performed Colonoscopy: A Four-group Randomized Controlled Tandem Colonoscopy Study

The goal of this clinical trial is to evaluate effect of artifial intelligent (AI) system, Endoscopy as AI-powered Device (ENAD) on adenoma miss rate from colonoscopy underwent by trainee endoscopist. It will also evaluate effect of AI on adenoma and polyp detection rate from colonoscopy underwent by trainee endoscopist. The main questions it aims to answer are:

Does AI-system lower adenoma miss rate in colonoscopy underwent by trainee endoscopist?

Researchers will do the tandem colonoscopy and devided the participant in 4 groups as follows:

First pass: trainee; Second pass: expert B. First pass: trainee + AI; Second pass: expert C. First pass: trainee; Second pass: expert + AI D. First pass: trainee+AI; Second pass: expert+AI Participants will take bowel preparation in split dose regimen and nothing per oral for 4 hours. They will underwent colonoscopy as above, with sedation by anesthesiologist. Details on qualities of colonoscopy, polyps detection and pathology results will be recorded.

Read the detailed description

Colon cancer accounts for one of the most common cancer worldwide and also cancer-related death. Colonoscopy is accepted to be an effective tool in colon cancer screening since the polypectomy of small adenoma can prevent colon cancer. Missed adenoma is one of the causes of interval cancer between routine colonoscopy screening. Nonvisualization is the cause of missed adenoma during colonoscopy. Artificial intelligence (AI)-assisted colonoscopy was superior then routine colonoscopy from parallel study and tandem study. Previous studies often used one same endoscopist in doing tandem colonoscopy which may still have bias. Only one previous study designed to use trainee endoscopist in the first pass and expert endoscopist in the second pass, some subgroups used AI-assisted. The result revealed the lower of adenoma miss rate (AMR) in AI-assisted colonoscopy in the first pass. This study designed to evaluate AMR of AI-assisted colonoscopy in trainee endoscopist compared to expert endoscopist, the trainee will do colonoscopy in the first pass (with or without AI) and the expert will do colonoscopy in the second pass (with or without AI). The present study aimed to evaluate effect of AI-assisted colonoscopy in trainee endoscopist.

Conditions: Artificial Intelligence (AI), Colonoscopy Education, Adenoma Colon Polyp
Being tested: Group A (Trainee --> expert), Group B (Trainee +AI --> expert), Group C (Trainee --> expert + AI), Group D (Trainee + AI --> expert + AI)
Keywords: Adenoma miss rate, Artificial intelligence, colonoscopy, tandem colonoscopy

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

Group A (Trainee --> expert)Device
The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy (white-light mode) without AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy (white-light mode) without AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent.
Group B (Trainee +AI --> expert)Device
The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy with AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy (white-light mode) without AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent.
Artificial intelligent (AI) assisted colonoscopy; ENdoscopy as AI-powered Device (ENAD) ENAD system (ENdoscopy as AI-powered Device, AINEX Corporation, Seoul, South Korea) is the system using CADe system (Computer-aided detection) which developed from 66,397 images and 8,756 polyps via deep learning-based object detection algorithm (YOLOv4) . It was validated by 15,753 images of polyp from 80 colonoscopy videos and 90,144 images of non-polyps from 50 colonoscopy videos. This system decreases false positive rate from 3.2% to 0.6% and increases sensitivity from 86.4% to 87.1%.
Group C (Trainee --> expert + AI)Device
The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy (white-light mode) without AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy with AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent.
Artificial intelligent (AI) assisted colonoscopy; ENdoscopy as AI-powered Device (ENAD) ENAD system (ENdoscopy as AI-powered Device, AINEX Corporation, Seoul, South Korea) is the system using CADe system (Computer-aided detection) which developed from 66,397 images and 8,756 polyps via deep learning-based object detection algorithm (YOLOv4) . It was validated by 15,753 images of polyp from 80 colonoscopy videos and 90,144 images of non-polyps from 50 colonoscopy videos. This system decreases false positive rate from 3.2% to 0.6% and increases sensitivity from 86.4% to 87.1%.
Group D (Trainee + AI --> expert + AI)Device
The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy with AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy with AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent.
Artificial intelligent (AI) assisted colonoscopy; ENdoscopy as AI-powered Device (ENAD) ENAD system (ENdoscopy as AI-powered Device, AINEX Corporation, Seoul, South Korea) is the system using CADe system (Computer-aided detection) which developed from 66,397 images and 8,756 polyps via deep learning-based object detection algorithm (YOLOv4) . It was validated by 15,753 images of polyp from 80 colonoscopy videos and 90,144 images of non-polyps from 50 colonoscopy videos. This system decreases false positive rate from 3.2% to 0.6% and increases sensitivity from 86.4% to 87.1%.

Study groups in NCT07023471
Study group	Role	What they receive
Group A (Trainee --> expert)	Placebo comparator	The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy without AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy without AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent. Receives: Device: Group A (Trainee --> expert)
Group B (Trainee +AI --> expert)	Other	The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy with AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy without AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent. Receives: Device: Group B (Trainee +AI --> expert)
Group C (Trainee --> expert + AI)	Other	The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy without AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy with AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent. Receives: Device: Group C (Trainee --> expert + AI)
Group D (Trainee + AI --> expert + AI)	Other	The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy with AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy with AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent. Receives: Device: Group D (Trainee + AI --> expert + AI)

What is being measured

The primary outcome is the main question the study is designed to answer.

Adenoma miss rate
Compare adenoma miss rate (AMR) in each groups including Non-AI/ Non-AI, Non-AI/ AI, AI/ Non-AI, and AI/ AI
Measured: Untill the end of procedure

Secondary outcomes (2)

Polyp miss rate
Compare polyp miss rate (PMR) in each groups
Measured: Untill the end of the procedure
Adenoma detection rate of colonoscopy underwent by the trainee
Compare adenoma detection rate (ADR) of colonoscopy underwent by trainee with or without AI
Measured: Untill the end of procedure of first pass which will be done by trainee

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

13 May 202531 Dec 2026

First posted17 Jun 2025
Study start13 May 2025
Primary completion13 May 2025
Study completion31 Dec 2026 (estimated)

Resources

Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
Other trials for Artificial Intelligence (AI)Studies of the same condition, open and under way.
What the trial phases meanHow a treatment moves from first tests in people to approval.

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design

Study type: Interventional
Phase: Phase N/A
Primary purpose: Diagnosis
Allocation: Randomised
Intervention model: Parallel groups
Masking: Triple blind
Who is masked: Participant, Investigator, Outcomes assessor
Enrolment: 364 participants (estimated)

IDs, dates and publications

ClinicalTrials.gov ID: NCT07023471
Sponsor's protocol ID: Si299/2025
Status last verified: Jun 2025
First submitted: 7 Jun 2025
Last updated: 24 Jun 2025
Results posted: No
Data monitoring committee: Yes
FDA-regulated drug: No
FDA-regulated device: No
Individual data sharing: Yes: The investigators are willing to provide our data to researchers who require it. For example, those who want to do systematic review and meta-analysis.

Interested in taking part?

The sponsor has not listed a contact. The official record may have more details.

Talk to your doctor first and take this page with you. Only the study team can confirm whether you can join.

Questions to ask the study team

What is the study trying to find out?
What would I need to do, and how often would I visit?
Could I receive a placebo instead of the treatment?
What are the possible risks and benefits for me?
Will it cost me anything? Are travel or time paid for?
Can I keep seeing my own doctor during the study?
What happens when the study ends?

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Study at a glance

From the registry record, last updated by the sponsor on 24 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.

Official title: Effect of an Artificial Intelligence-assisted Colonoscopy on Adenoma Miss Rate of Trainee-performed Colonoscopy: A Four-group Randomized Controlled Tandem Colonoscopy Study
ClinicalTrials.gov ID: NCT07023471
Acronym / sponsor ID: Si299/2025
Conditions: Artificial Intelligence (AI), Colonoscopy Education, Adenoma Colon Polyp
Keywords: Adenoma miss rate, Artificial intelligence, colonoscopy, tandem colonoscopy
Study type: Interventional
Recruitment status: Enrolling by invitation
Enrolment: 364 participants (estimated)
Lead sponsor: Mahidol UniversityUniversity, hospital or other
Study start: 13 May 2025 (actual)
Primary completion: 13 May 2025 (actual)
Study completion: 31 Dec 2026 (estimated)
First posted: 17 Jun 2025 (actual)
Results: Not posted in the source record

Clinical summary

The research question as the sponsor registered it. This describes what the study plans to test, not what it found.

Does AI-system lower adenoma miss rate in colonoscopy underwent by trainee endoscopist?

Researchers will do the tandem colonoscopy and devided the participant in 4 groups as follows:

First pass: trainee; Second pass: expert B. First pass: trainee + AI; Second pass: expert C. First pass: trainee; Second pass: expert + AI D. First pass: trainee+AI; Second pass: expert+AI Participants will take bowel preparation in split dose regimen and nothing per oral for 4 hours. They will underwent colonoscopy as above, with sedation by anesthesiologist. Details on qualities of colonoscopy, polyps detection and pathology results will be recorded.

Detailed description

Study design

Primary purpose: Diagnosis
Allocation: Randomised
Intervention model: Parallel groups
Masking: Triple blind (participant, investigator, outcomes assessor)
Number of arms: 4

Arm	Type	Receives
Group A (Trainee --> expert)	Placebo comparator	Device: Group A (Trainee --> expert)The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy without AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy without AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent.
Group B (Trainee +AI --> expert)	Other	Device: Group B (Trainee +AI --> expert)The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy with AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy without AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent.
Group C (Trainee --> expert + AI)	Other	Device: Group C (Trainee --> expert + AI)The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy without AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy with AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent.
Group D (Trainee + AI --> expert + AI)	Other	Device: Group D (Trainee + AI --> expert + AI)The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy with AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy with AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent.

Who may qualify

Ages: 40 to 85 years
Sex: All
Healthy volunteers: Not accepted
Age groups: Adult, Older adult

Key inclusion criteria (2 listed)

Age 40 - 85 years old
Appointment for colonoscopy for colorectal cancer screening

Key exclusion criteria (6 listed)

Previous history of bowel obstruction or perforation
Presence of coagulopathy (Prothrombin time >, = 3 second ULN; Platelet < 50,000)
Previously diagnosed with inflammatory bowel disease or polyposis syndrome
Pregnancy or lactation
Severe comorbities or American Society of Anesthesiologist classification >, = 3

Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.

Interventions

Intervention	Type	Arms
Group A (Trainee --> expert)The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy (white-light mode) without AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy (white-light mode) without AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent.	Device	Group A (Trainee --> expert)
Group B (Trainee +AI --> expert)The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy with AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy (white-light mode) without AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent. Artificial intelligent (AI) assisted colonoscopy; ENdoscopy as AI-powered Device (ENAD) ENAD system (ENdoscopy as AI-powered Device, AINEX Corporation, Seoul, South Korea) is the system using CADe system (Computer-aided detection) which developed from 66,397 images and 8,756 polyps via deep learning-based object detection algorithm (YOLOv4) . It was validated by 15,753 images of polyp from 80 colonoscopy videos and 90,144 images of non-polyps from 50 colonoscopy videos. This system decreases false positive rate from 3.2% to 0.6% and increases sensitivity from 86.4% to 87.1%.	Device	Group B (Trainee +AI --> expert)
Group C (Trainee --> expert + AI)The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy (white-light mode) without AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy with AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent. Artificial intelligent (AI) assisted colonoscopy; ENdoscopy as AI-powered Device (ENAD) ENAD system (ENdoscopy as AI-powered Device, AINEX Corporation, Seoul, South Korea) is the system using CADe system (Computer-aided detection) which developed from 66,397 images and 8,756 polyps via deep learning-based object detection algorithm (YOLOv4) . It was validated by 15,753 images of polyp from 80 colonoscopy videos and 90,144 images of non-polyps from 50 colonoscopy videos. This system decreases false positive rate from 3.2% to 0.6% and increases sensitivity from 86.4% to 87.1%.	Device	Group C (Trainee --> expert + AI)
Group D (Trainee + AI --> expert + AI)The expert endoscopist insert to cecum in both passes. First pass: Trainee withdraw colonoscopy with AI. The polyps detected can be removed as suitable. The pathology for polyp will be sent. Second pass: Expert withdraw colonoscopy with AI. The polyps detected (which is missed from the first pass) can be removed as suitable. The pathology for polyp will be sent. Artificial intelligent (AI) assisted colonoscopy; ENdoscopy as AI-powered Device (ENAD) ENAD system (ENdoscopy as AI-powered Device, AINEX Corporation, Seoul, South Korea) is the system using CADe system (Computer-aided detection) which developed from 66,397 images and 8,756 polyps via deep learning-based object detection algorithm (YOLOv4) . It was validated by 15,753 images of polyp from 80 colonoscopy videos and 90,144 images of non-polyps from 50 colonoscopy videos. This system decreases false positive rate from 3.2% to 0.6% and increases sensitivity from 86.4% to 87.1%.	Device	Group D (Trainee + AI --> expert + AI)

Primary outcome

Adenoma miss rate
Time frame: Untill the end of procedure
Compare adenoma miss rate (AMR) in each groups including Non-AI/ Non-AI, Non-AI/ AI, AI/ Non-AI, and AI/ AI

2 secondary outcomes

Polyp miss rate
Time frame: Untill the end of the procedure
Adenoma detection rate of colonoscopy underwent by the trainee
Time frame: Untill the end of procedure of first pass which will be done by trainee

Results and safety

This study is still under way. Results are not available in the source record yet.

Research links

Official record on ClinicalTrials.govLast updated by the sponsor 24 Jun 2025.
Individual participant dataSharing planned: Yes. The investigators are willing to provide our data to researchers who require it. For example, those who want to do systematic review and meta-analysis.

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Referral and contact

AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.

The record lists no contact. Use the official record to reach the sponsor.

1 site in 1 country: see every site and its status.

Questions about this trial

What is this clinical trial studying?

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 2 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: enrolling by invitation, as of the sponsor's last update on 24 Jun 2025. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in Thailand. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. Some participants in this study may receive a placebo. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Adenoma miss rate (time frame: Untill the end of procedure). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT07023471.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Jun 2025.