Using AI to improve cancer risk assessment and treatment outcomes
Development and Demonstration of Intelligent Assessment Based on Multi-modal Information Fusion for Tumor Risk and Diagnosis and Treatment
This study is testing if using artificial intelligence to analyze a wide range of medical data can help predict cancer risks and improve treatment for people with suspected cancers and healthy individuals.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 3000 (estimated) |
| Ages | 18 Years to 75 Years |
| Sex | All |
| Sponsor | Union Hospital, Tongji Medical College, Huazhong University of Science and Technology Academic / other |
| Locations | 1 site (Wuhan, Hubei) |
| Trial ID | NCT06653478 on ClinicalTrials.gov |
What this trial studies
This study aims to enhance the accuracy of cancer risk prediction and treatment outcomes by establishing a comprehensive medical database that includes clinical, imaging, and multi-omics data for common tumors such as lung and stomach cancers. It will utilize artificial intelligence to develop a multi-modal data fusion technology system that analyzes this extensive dataset. The focus is on creating individualized diagnostic and treatment prediction models while addressing challenges like data imbalance and interpretability. The study will involve both patients with suspected cancers and healthy participants to build a robust dataset.
Who should consider this trial
Good fit: Ideal candidates include individuals suspected of having lung cancer, stomach cancer, or colorectal cancer, as well as healthy participants for comparative analysis.
Not a fit: Patients with incomplete clinical data or those who are lost to follow-up may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to more accurate cancer diagnoses and personalized treatment plans for patients.
How similar studies have performed: While the use of AI in cancer diagnosis is gaining traction, this specific approach of multi-modal data fusion is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Participants with the suspected of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision 2. Participants that have signed informed consent. 3. Participants with detailed electronic medical records, image records, pathological records, multi-omics information, and other important clinical diagnostic information. 4. Healthy participants with no clinical diagnosis of lung cancer/node, or stomach cancer/lesion, or colorectal cancer/leision. Exclusion Criteria: 1. Participants with primary clinical and pathological data missing. 2. Participants lost to follow-up. 3. Participants with too poor medical image quality to perform segment and mark ROI accurately
Where this trial is running
Wuhan, Hubei
- Wuhan Union Hospital — Wuhan, Hubei, China (Recruiting)
Study contacts
- Principal investigator: Yang Jin — Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
- Study coordinator: Juanjuan Xu
- Email: whuhjy@126.com
- Phone: +86 15827125538
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.