Colorectal CancerNCT07815093
Multimodal Artificial Intelligence for Non-Invasive Colorectal Cancer Screening Based on Holographic Biology
An observational study of Colorectal Cancer, run by Xiuli Zuo.
Trial summary
The purpose of this study is to propose a non-invasive screening method by integrating holographic biological theory and artificial intelligence technology. A colorectal cancer risk assessment model will be constructed by analyzing multimodal data including facial features, tongue image characteristics and exhaled… Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Colorectal Cancer
- What is being tested?
- Multimodal non-invasive detection for colorectal cancer
- How many people
- 11,000 participants
- Where
- No sites listed yet
- Study dates
- 1 Oct 2026to 1 Jul 2028
- How long will I take part?
- 1 Day
- Phase
- Observational
- 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 18 to 80 years
- All sexes
- Adult, Older adult
Study population: Participants aged 18-80 years who are scheduled to undergo colonoscopy. All participants provide informed consent. This study enrolls subjects preparing for colonoscopic examination to collect multimodal data for constructing an artificial intelligence-based colorectal cancer risk assessment model.
Who may be able to join
- Patients aged 18-80 years scheduled to undergo colonoscopy.
- All patients provide informed consent and sign the informed consent form.
Who cannot join
- Patients with severe cardiac, cerebral, pulmonary or renal dysfunction, or psychiatric disorders that prevent colonoscopy;
- Patients with a history of gastrointestinal surgery;
- Patients taking bismuth agents or other staining medications.
About this study
Official title: Multimodal Artificial Intelligence for Non-Invasive Colorectal Cancer Screening Based on Holographic Biology.
The purpose of this study is to propose a non-invasive screening method by integrating holographic biological theory and artificial intelligence technology. A colorectal cancer risk assessment model will be constructed by analyzing multimodal data including facial features, tongue image characteristics and exhaled gas. The hypothesis of this study is that the model can attain both sensitivity and specificity of 80%.This study will enroll patients aged 18-80 years scheduled to undergo colonoscopy. All participants shall provide informed consent and sign the informed consent form. Patients will be excluded if they have severe cardiac, cerebral, pulmonary or renal dysfunction, or psychiatric disorders precluding colonoscopy, have a history of gastrointestinal surgery, or have taken bismuth agents or other staining medications. Based on estimates from existing literature, the training set will require tongue images, facial images, exhaled gas analysis results and colonoscopic diagnoses from 5000 patients, and the test set will require such data from 6000 patients.
- Conditions
- Colorectal Cancer
- Being tested
- Multimodal non-invasive detection for colorectal cancer
- Medical subject headings
- Colorectal Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Multimodal non-invasive detection for colorectal cancerOther
Collection of facial images, tongue images and exhaled gas data from participants. No therapeutic intervention is performed. The collected multimodal data will be used to build an artificial intelligence-based colorectal cancer risk assessment model.
What is being measured
The primary outcome is the main question the study is designed to answer.
Presence of colonic polyps and colorectal cancer.
Measured: At the time of enrollment and colonoscopy examination
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Sep 2026
- Study start1 Oct 2026 (estimated)
- Primary completion1 Apr 2028 (estimated)
- Study completion1 Jul 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Colorectal CancerStudies 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
- Observational
- Observational model
- Other
- Time perspective
- Other
- Enrolment
- 11,000 participants (estimated)
- Target duration
- 1 Day
Sponsor and investigators
- Lead sponsor
- Xiuli Zuo
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Xiuli Zuo, Shandong University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07815093
- Sponsor's protocol ID
- KYLL-2026-06-037-1
- Status last verified
- Sep 2026
- First submitted
- 6 Sep 2026
- Last updated
- 11 Sep 2026
- Results posted
- No
Study at a glance
From the registry record, last updated by the sponsor on 11 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multimodal Artificial Intelligence for Non-Invasive Colorectal Cancer Screening Based on Holographic Biology.
- ClinicalTrials.gov ID
- NCT07815093
- Acronym / sponsor ID
- KYLL-2026-06-037-1
- Conditions
- Colorectal Cancer
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 11,000 participants (estimated)
- Lead sponsor
- Xiuli ZuoUniversity, hospital or other
- Study start
- 1 Oct 2026 (estimated)
- Primary completion
- 1 Apr 2028 (estimated)
- Study completion
- 1 Jul 2028 (estimated)
- First posted
- 11 Sep 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 purpose of this study is to propose a non-invasive screening method by integrating holographic biological theory and artificial intelligence technology. A colorectal cancer risk assessment model will be constructed by analyzing multimodal data including facial features, tongue image characteristics and exhaled gas. The hypothesis of this study is that the model can attain both sensitivity and specificity of 80%.This study will enroll patients aged 18-80 years scheduled to undergo colonoscopy. All participants shall provide informed consent and sign the informed consent form. Patients will be excluded if they have severe cardiac, cerebral, pulmonary or renal dysfunction, or psychiatric disorders precluding colonoscopy, have a history of gastrointestinal surgery, or have taken bismuth agents or other staining medications. Based on estimates from existing literature, the training set will require tongue images, facial images, exhaled gas analysis results and colonoscopic diagnoses from 5000 patients, and the test set will require such data from 6000 patients.
Study design
- Observational model
- Other
- Time perspective
- Other
- Target follow-up
- 1 Day
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Participants aged 18-80 years who are scheduled to undergo colonoscopy. All participants provide informed consent. This study enrolls subjects preparing for colonoscopic examination to collect multimodal data for constructing an artificial intelligence-based colorectal cancer risk assessment model.
Key inclusion criteria (2 listed)
- Patients aged 18-80 years scheduled to undergo colonoscopy.
- All patients provide informed consent and sign the informed consent form.
Key exclusion criteria (3 listed)
- Patients with severe cardiac, cerebral, pulmonary or renal dysfunction, or psychiatric disorders that prevent colonoscopy;
- Patients with a history of gastrointestinal surgery;
- Patients taking bismuth agents or other staining medications.
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 |
|---|---|---|
| Multimodal non-invasive detection for colorectal cancerCollection of facial images, tongue images and exhaled gas data from participants. No therapeutic intervention is performed. The collected multimodal data will be used to build an artificial intelligence-based colorectal cancer risk assessment model. | Other | – |
Primary outcome
Presence of colonic polyps and colorectal cancer.
Time frame: At the time of enrollment and colonoscopy examination
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 11 Sep 2026.
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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.
Questions about this trial
What is this clinical trial studying?
An observational study of Colorectal Cancer, run by Xiuli Zuo.
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 3 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: opening soon, as of the sponsor's last update on 11 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
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?
Presence of colonic polyps and colorectal cancer. (time frame: At the time of enrollment and colonoscopy examination). 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 11 Sep 2026.