AI App Improves Bowel Preparation Quality for ColonoscopyNCT07453056
The Efficacy of AI-Driven Feces Identification for Bowel Preparation Prior to Colonoscopy
A study testing A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven feces identifying for the Bowel Preparation Prior to Colonoscopy and educational leaflet without APP in people with AI App Improves Bowel Preparation Quality for Colonoscopy, run by Fu Jen Catholic University Hospital at 1 site in Taiwan.
Trial summary
The objective is to enhance diagnostic outcomes by ensuring thorough bowel cleanliness through AI-driven stool identifying system for bowel preparation in subjects undergoing colonoscopy.Colonoscopy is a key procedure for the prevention and early detection of colorectal cancer, with its diagnostic accuracy highly… Read more about this study
- Who is it for?
- Ages 20 to 60 yearsHealthy volunteers can take part
- Conditions the study is for
- AI App Improves Bowel Preparation Quality for Colonoscopy
- What is being tested?
- A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven feces identifying for the Bowel Preparation Prior to Colonoscopy and educational leaflet without APP
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 340 participants
- Where
- 1 siteTaiwan
- Study dates
- 4 Sep 2025to 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 20 to 60 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- Men or women 20 and 60 years of age.
- Subject who are scheduled for colonoscopy.
- Ability to complete the entire procedure and to comply with study instructions.
- Will provide completed and signed written informed consents
Who cannot join
- 1. Patients who are unsuitable for Bowklean use due to known contraindications, including but not limited to:
- Allergies or hypersensitivity to Bowklean or its ingredients.
- Severe gastrointestinal conditions (e.g., obstruction, perforation).
- Renal impairment or electrolyte imbalances (e.g., severe hyponatremia).
- Recent gastrointestinal surgery affecting bowel preparation. 2. Cognitive, language, or other barriers that prevent completion of the questionnaire.
- 3. Non-compliance with the bowel preparation protocol or inability to follow dietary restrictions (e.g., Prepackaged low residue diet, PLD).
Trial locations and contacts
1 site in 1 country.
Taiwan1 site
Fu Jen Catholic University Hospital
New Taipei City, Taishan District, 243
About this study
Official title: A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven Feces Identifying for the Bowel Preparation Prior to Colonoscopy
The objective is to enhance diagnostic outcomes by ensuring thorough bowel cleanliness through AI-driven stool identifying system for bowel preparation in subjects undergoing colonoscopy.Colonoscopy is a key procedure for the prevention and early detection of colorectal cancer, with its diagnostic accuracy highly dependent on the quality of bowel preparation. Inadequate bowel cleansing can lead to missed lesions, prolonged procedure times, and the need for repeat examinations. Despite public health efforts that have improved screening rates over the past decade, the adequacy of bowel preparation has remained relatively unchanged, posing a persistent clinical challenge.
With the rapid advancement of artificial intelligence (AI) technologies, deep learning-based image recognition has demonstrated outstanding performance in medical imaging applications. Recent studies have shown that AI can assist in real-time evaluation of stool appearance, providing patients with immediate feedback and personalized instructions to improve bowel preparation quality. Integrating AI systems into bowel cleansing protocols has the potential to enhance patient compliance, optimize bowel cleanliness, and consequently improve the diagnostic yield of colonoscopy.
This study aims to evaluate the efficacy of an AI-based stool identifying system (AI-SIS), combined with the use of a Prepackaged Low Residue Diet (PLD) and standard bowel preparation instructions. Through a prospective, randomized, evaluator-blind, parallel-group clinical trial design, the study seeks to generate scientific evidence supporting the integration of AI technology into routine bowel preparation practices.
Read the detailed description
Bowel preparation is the process of removing all stools from the colon in order to have a medical or surgical procedure such as a colonoscopy. It is important to clean the colon of all stools, food particles and anything else that may be present for several reasons. If you are having surgery on or near the colon, having stools presented is a risk for infection and can get in the way of some procedures. There are times when bowel preparation is done purely to prevent potential complications from surgery. For example, if your bowel was nicked during surgery, the infection risk would be dramatically decreased if the bowel was empty. In the case of a colonoscopy, stool in the colon can prevent the surgeon from seeing the tissue that is being inspected and would make it very difficult to introduce the lighted scope into the rectum and colon.
Colonoscopies have been shown to help reduce the incidence of colon cancer and deaths associated with the disease. Over the last decade, public health initiatives have helped drive up the rate of screenings, yet the current rates still fall short of public health targets set forth. Concurrently, the rate of adequate preparing for screening which is associated with colonoscopy effectiveness has changed little over the last 10 years.
With rapid advancements in artificial intelligence (AI), image recognition techniques have emerged as particularly valuable tools in medical applications. Deep learning algorithms, a subfield of AI, have demonstrated impressive performance in analyzing and categorizing complex medical imaging data, enabling efficient real-time decision support in clinical settings. Recent studies have highlighted the promising application of AI-driven image recognition in evaluating stool appearance and bowel cleanliness, providing immediate feedback and personalized instructions to patients undergoing bowel preparation. Incorporating such AI system has the potential to significantly enhance patient compliance, improve bowel preparation effectiveness, and consequently, increase diagnostic accuracy and the overall clinical value of colonoscopy procedures .This study is a prospective, randomized, evaluator-blind, parallel-group clinical trial designed to evaluate the efficacy of an AI-SIS in improving bowel preparation prior to colonoscopy. Participants will be randomly assigned in a 1:1 ratio into two groups, with approximately 170 participants per group, totaling 340 participants.
Group A (Intervention group): Participants will utilize the AI-SIS, designed to provide real-time feedback on bowel cleanliness through image classification of stool into three categories (Grade A: adequate cleansing; Grade B or C: inadequate cleansing requiring further bowel preparation). In addition to the standard hospital-provided educational instructions, this group will use the AI-SIS.
Group B (Control group): Participants will undergo standard bowel preparation and receive only the standard hospital-provided educational instructions without the assistance of the AI-SIS.
All participants will use Bowklean® during the bowel preparation process and adhere to dietary control using a Prepackaged Low Residue Diet (PLD). Both groups will receive identical standard in-hospital educational instructions regarding bowel preparation procedures. Additionally, participants from either group can call an 0800 toll-free hotline for consultation if they encounter any issues during the preparation.
Evaluator blinding will be maintained, with bowel cleanliness assessed using the Boston Bowel Preparation Scale (BBPS). Colonoscopy procedures and subsequent evaluations will be performed by independent, blinded colonoscopists to ensure objective and unbiased results.
- Being tested
- A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven feces identifying for the Bowel Preparation Prior to Colonoscopy, educational leaflet without APP
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven feces identifying for the Bowel Preparation Prior to ColonoscopyOther
educational leaflet and APP for reaching AI-SIS for AI aid
educational leaflet without APPOther
educational leaflet without APP
| Study group | Role | What they receive |
|---|---|---|
| Group A：educational leaflet and APP for reaching AI-SIS for AI aid | Experimental | educational leaflet and APP for reaching AI-SIS for AI aid Receives: Other: A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven feces identifying for the Bowel Preparation Prior to Colonoscopy |
| Group B：educational leaflet without APP | Active comparator | educational leaflet without APP Receives: Other: educational leaflet without APP |
What is being measured
The primary outcome is the main question the study is designed to answer.
Primary Outcome Measure
The percentage of subjects achieving adequate bowel cleansing, represented by a score of each segment ≥2 or higher on the BBPS.
Measured: 45 days
Secondary outcomes (1)
Secondary Outcome Measure
The percentage of subjects that achieve excellent cleansing (score ≧ 8) in the Boston Bowel Preparation Scale (BBPS).
Mean score in different colon segments (right, transverse, left), which are assessed with the BBPS.
Polyp detection rate, Adenomas detected rate, and Advanced adenomas detected rate Withdrawal time from cecal Comparing toll-free call rate of each group. Subject's satisfaction to the AI-SIS. Subject's satisfaction to the Prepackaged low residue diet (PLD). For this section, the measurements will be conducted as follows: after completion of the examination, the endoscopist will assess the bowel cleanliness score, and participants will complete a post-use satisfaction questionnaire.
Measured: 45 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Mar 2026
- Study start4 Sep 2025
- Primary completion28 Mar 2026
- Study completionDec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for AI App Improves Bowel Preparation Quality for ColonoscopyStudies 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
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 340 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Fu Jen Catholic University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07453056
- Sponsor's protocol ID
- FJUH114465
- Status last verified
- Jul 2026
- First submitted
- 12 Feb 2026
- Last updated
- 21 Jul 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven Feces Identifying for the Bowel Preparation Prior to Colonoscopy
- ClinicalTrials.gov ID
- NCT07453056
- Acronym / sponsor ID
- FJUH114465
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 340 participants (estimated)
- Lead sponsor
- Fu Jen Catholic University HospitalUniversity, hospital or other
- Study start
- 4 Sep 2025 (actual)
- Primary completion
- 28 Mar 2026 (actual)
- Study completion
- Dec 2026 (estimated)
- First posted
- 5 Mar 2026 (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.
The objective is to enhance diagnostic outcomes by ensuring thorough bowel cleanliness through AI-driven stool identifying system for bowel preparation in subjects undergoing colonoscopy.Colonoscopy is a key procedure for the prevention and early detection of colorectal cancer, with its diagnostic accuracy highly dependent on the quality of bowel preparation. Inadequate bowel cleansing can lead to missed lesions, prolonged procedure times, and the need for repeat examinations. Despite public health efforts that have improved screening rates over the past decade, the adequacy of bowel preparation has remained relatively unchanged, posing a persistent clinical challenge.
With the rapid advancement of artificial intelligence (AI) technologies, deep learning-based image recognition has demonstrated outstanding performance in medical imaging applications. Recent studies have shown that AI can assist in real-time evaluation of stool appearance, providing patients with immediate feedback and personalized instructions to improve bowel preparation quality. Integrating AI systems into bowel cleansing protocols has the potential to enhance patient compliance, optimize bowel cleanliness, and consequently improve the diagnostic yield of colonoscopy.
This study aims to evaluate the efficacy of an AI-based stool identifying system (AI-SIS), combined with the use of a Prepackaged Low Residue Diet (PLD) and standard bowel preparation instructions. Through a prospective, randomized, evaluator-blind, parallel-group clinical trial design, the study seeks to generate scientific evidence supporting the integration of AI technology into routine bowel preparation practices.
Detailed description
Bowel preparation is the process of removing all stools from the colon in order to have a medical or surgical procedure such as a colonoscopy. It is important to clean the colon of all stools, food particles and anything else that may be present for several reasons. If you are having surgery on or near the colon, having stools presented is a risk for infection and can get in the way of some procedures. There are times when bowel preparation is done purely to prevent potential complications from surgery. For example, if your bowel was nicked during surgery, the infection risk would be dramatically decreased if the bowel was empty. In the case of a colonoscopy, stool in the colon can prevent the surgeon from seeing the tissue that is being inspected and would make it very difficult to introduce the lighted scope into the rectum and colon.
Colonoscopies have been shown to help reduce the incidence of colon cancer and deaths associated with the disease. Over the last decade, public health initiatives have helped drive up the rate of screenings, yet the current rates still fall short of public health targets set forth. Concurrently, the rate of adequate preparing for screening which is associated with colonoscopy effectiveness has changed little over the last 10 years.
With rapid advancements in artificial intelligence (AI), image recognition techniques have emerged as particularly valuable tools in medical applications. Deep learning algorithms, a subfield of AI, have demonstrated impressive performance in analyzing and categorizing complex medical imaging data, enabling efficient real-time decision support in clinical settings. Recent studies have highlighted the promising application of AI-driven image recognition in evaluating stool appearance and bowel cleanliness, providing immediate feedback and personalized instructions to patients undergoing bowel preparation. Incorporating such AI system has the potential to significantly enhance patient compliance, improve bowel preparation effectiveness, and consequently, increase diagnostic accuracy and the overall clinical value of colonoscopy procedures .This study is a prospective, randomized, evaluator-blind, parallel-group clinical trial designed to evaluate the efficacy of an AI-SIS in improving bowel preparation prior to colonoscopy. Participants will be randomly assigned in a 1:1 ratio into two groups, with approximately 170 participants per group, totaling 340 participants.
Group A (Intervention group): Participants will utilize the AI-SIS, designed to provide real-time feedback on bowel cleanliness through image classification of stool into three categories (Grade A: adequate cleansing; Grade B or C: inadequate cleansing requiring further bowel preparation). In addition to the standard hospital-provided educational instructions, this group will use the AI-SIS.
Group B (Control group): Participants will undergo standard bowel preparation and receive only the standard hospital-provided educational instructions without the assistance of the AI-SIS.
All participants will use Bowklean® during the bowel preparation process and adhere to dietary control using a Prepackaged Low Residue Diet (PLD). Both groups will receive identical standard in-hospital educational instructions regarding bowel preparation procedures. Additionally, participants from either group can call an 0800 toll-free hotline for consultation if they encounter any issues during the preparation.
Evaluator blinding will be maintained, with bowel cleanliness assessed using the Boston Bowel Preparation Scale (BBPS). Colonoscopy procedures and subsequent evaluations will be performed by independent, blinded colonoscopists to ensure objective and unbiased results.
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Group A：educational leaflet and APP for reaching AI-SIS for AI aid | Experimental | Other: A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven feces identifying for the Bowel Preparation Prior to Colonoscopyeducational leaflet and APP for reaching AI-SIS for AI aid |
| Group B：educational leaflet without APP | Active comparator | Other: educational leaflet without APPeducational leaflet without APP |
Who may qualify
- Ages
- 20 to 60 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (4 listed)
- Men or women 20 and 60 years of age.
- Subject who are scheduled for colonoscopy.
- Ability to complete the entire procedure and to comply with study instructions.
- Will provide completed and signed written informed consents
Key exclusion criteria (6 listed)
- 1. Patients who are unsuitable for Bowklean use due to known contraindications, including but not limited to:
- Allergies or hypersensitivity to Bowklean or its ingredients.
- Severe gastrointestinal conditions (e.g., obstruction, perforation).
- Renal impairment or electrolyte imbalances (e.g., severe hyponatremia).
- Recent gastrointestinal surgery affecting bowel preparation. 2. Cognitive, language, or other barriers that prevent completion of the questionnaire.
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 |
|---|---|---|
| A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven feces identifying for the Bowel Preparation Prior to Colonoscopyeducational leaflet and APP for reaching AI-SIS for AI aid | Other | Group A：educational leaflet and APP for reaching AI-SIS for AI aid |
| educational leaflet without APPeducational leaflet without APP | Other | Group B：educational leaflet without APP |
Primary outcome
Primary Outcome Measure
Time frame: 45 days
The percentage of subjects achieving adequate bowel cleansing, represented by a score of each segment ≥2 or higher on the BBPS.
1 secondary outcome
Secondary Outcome Measure
Time frame: 45 days
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 21 Jul 2026.
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. This study is not recruiting at the moment.
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?
A study testing A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven feces identifying for the Bowel Preparation Prior to Colonoscopy and educational leaflet without APP in people with AI App Improves Bowel Preparation Quality for Colonoscopy, run by Fu Jen Catholic University Hospital at 1 site in Taiwan.
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 4 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: under way, not looking for participants, as of the sponsor's last update on 21 Jul 2026. 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 Taiwan. 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. 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?
Primary Outcome Measure (time frame: 45 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 21 Jul 2026.