Colorectal PolypsNCT06610630
Research on the Application of AI Image Recognition-Based Smartphone Apps in Personalized Bowel Preparation
A study testing Assessment of Bowel Preparation Using AI-Driven Smartphone Applications in people with Colorectal Polyps, run by Jianning Yao at 1 site in China.
Trial summary
Colorectal cancer, as one of the most common malignant tumors of the digestive system, has a high incidence and mortality rate worldwide. High-quality colonoscopy is essential for the early detection and prevention of colorectal cancer and is key to improving the survival rates of patients. Read more about this study
- Who is it for?
- Ages 18 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Colorectal Polyps
- What is being tested?
- Assessment of Bowel Preparation Using AI-Driven Smartphone Applications
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 513 participants
- Where
- 1 siteChina
- Study dates
- 1 Oct 2024to 31 Mar 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 18 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Patients who underwent painless colonoscopy at the Digestive Endoscopy Center of the First Affiliated Hospital of Zhengzhou University and signed the informed consent for the clinical trial.
- Individuals who use smartphones.
Who cannot join
- Patients with contraindications for colonoscopy. Individuals in whom successful cecal intubation could not be achieved.
Trial locations and contacts
1 site in 1 country.
China1 site
The First Affiliated Hospital of Zhengzhou University
Zhengzhou, Henan, 450052
About this study
Colorectal cancer, as one of the most common malignant tumors of the digestive system, has a high incidence and mortality rate worldwide. High-quality colonoscopy is essential for the early detection and prevention of colorectal cancer and is key to improving the survival rates of patients. However, traditional colonoscopy faces numerous challenges in bowel preparation, such as inadequate preparation and a lack of personalized cleansing approaches. Therefore, it is particularly important to develop timely and efficient individualized bowel preparation methods. Artificial intelligence, especially deep learning technologies, has shown great potential in the medical field. This study aims to leverage the advantages of artificial intelligence to optimize the bowel preparation process before colonoscopy, creating a personalized bowel preparation plan that effectively improves the efficacy of colorectal cancer screening and diagnosis.
- Conditions
- Colorectal Polyps
- Being tested
- Assessment of Bowel Preparation Using AI-Driven Smartphone Applications
- Keywords
- Colonoscopy, bowel preparation, artificial intelligence, smartphone, BBPS score
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Assessment of Bowel Preparation Using AI-Driven Smartphone ApplicationsDiagnostic test
Assessment of Bowel Preparation Using AI-Driven Smartphone Applications
| Study group | Role | What they receive |
|---|---|---|
| AI-assisted group | Experimental | Not described Receives: Diagnostic Test: Assessment of Bowel Preparation Using AI-Driven Smartphone Applications |
| Conventional control group | No intervention | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Boston Bowel Preparation Scale
Measured: During Colonoscopy
Dosage of Bowel Cleansing Agents
Measured: During Bowel Preparation Before Colonoscopy
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Sep 2024
- Study start1 Oct 2024
- Primary completion31 Mar 2025
- Study completion31 Mar 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Colorectal PolypsStudies 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
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 513 participants (actual)
Sponsor and investigators
- Lead sponsor
- Jianning Yao
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Jianning Yao, The First Affiliated Hospital of Zhengzhou University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06610630
- Sponsor's protocol ID
- 2024-KY-1219-001
- Status last verified
- May 2025
- First submitted
- 21 Sep 2024
- Last updated
- 14 May 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Han F, Gao S, Zhan H, Wang N, Song Z, Xie J, Hou Y, Deng Y, Yao J. Use of an AI Image Recognition-Based Smartphone App in Personalized Bowel Preparation Before Colonoscopy: Prospective Randomized Controlled Trial. JMIR Mhealth Uhealth. 2026 Jul 14;14:e77701. doi: 10.2196/77701.
PubMed 42447478
Study at a glance
From the registry record, last updated by the sponsor on 14 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Research on the Application of AI Image Recognition-Based Smartphone Apps in Personalized Bowel Preparation
- ClinicalTrials.gov ID
- NCT06610630
- Acronym / sponsor ID
- 2024-KY-1219-001
- Conditions
- Colorectal Polyps
- Keywords
- Colonoscopy, bowel preparation, artificial intelligence, smartphone, BBPS score
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 513 participants (actual)
- Lead sponsor
- Jianning YaoUniversity, hospital or other
- Study start
- 1 Oct 2024 (actual)
- Primary completion
- 31 Mar 2025 (actual)
- Study completion
- 31 Mar 2025 (actual)
- First posted
- 24 Sep 2024 (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.
Colorectal cancer, as one of the most common malignant tumors of the digestive system, has a high incidence and mortality rate worldwide. High-quality colonoscopy is essential for the early detection and prevention of colorectal cancer and is key to improving the survival rates of patients. However, traditional colonoscopy faces numerous challenges in bowel preparation, such as inadequate preparation and a lack of personalized cleansing approaches. Therefore, it is particularly important to develop timely and efficient individualized bowel preparation methods. Artificial intelligence, especially deep learning technologies, has shown great potential in the medical field. This study aims to leverage the advantages of artificial intelligence to optimize the bowel preparation process before colonoscopy, creating a personalized bowel preparation plan that effectively improves the efficacy of colorectal cancer screening and diagnosis.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-assisted group | Experimental | Diagnostic Test: Assessment of Bowel Preparation Using AI-Driven Smartphone Applications |
| Conventional control group | No intervention | – |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Patients who underwent painless colonoscopy at the Digestive Endoscopy Center of the First Affiliated Hospital of Zhengzhou University and signed the informed consent for the clinical trial.
- Individuals who use smartphones.
Key exclusion criteria (1 listed)
- Patients with contraindications for colonoscopy. Individuals in whom successful cecal intubation could not be achieved.
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 |
|---|---|---|
| Assessment of Bowel Preparation Using AI-Driven Smartphone ApplicationsAssessment of Bowel Preparation Using AI-Driven Smartphone Applications | Diagnostic test | AI-assisted group |
Primary outcome
Boston Bowel Preparation Scale
Time frame: During Colonoscopy
Dosage of Bowel Cleansing Agents
Time frame: During Bowel Preparation Before Colonoscopy
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 14 May 2025.
- Derived from this study: PubMed 42447478Han F, Gao S, Zhan H, Wang N, Song Z, Xie J, Hou Y, Deng Y, Yao J. Use of an AI Image Recognition-Based Smartphone App in Personalized Bowel Preparation Before Colonoscopy: Prospective Randomized Controlled Trial. JMIR Mhealth Uhealth. 2026 Jul 14;14:e77701. doi: 10.2196/77701.
- Individual participant dataSharing planned: No
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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. 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 Assessment of Bowel Preparation Using AI-Driven Smartphone Applications in people with Colorectal Polyps, run by Jianning Yao at 1 site in China.
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 1 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: finished, as of the sponsor's last update on 14 May 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 China. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
Boston Bowel Preparation Scale (time frame: During Colonoscopy). The study lists 2 primary outcomes in all. 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 NCT06610630, which also lists 1 linked publication.
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 14 May 2025.