AI-based prediction of five major diseases using integrated health data
Official title: AI-Based Phenome Data Analysis for Predicting the Onset of Major Diseases
Run by Asan Medical Center · NCT07595718 · Data updated 2026-11-12
Researchers are testing an AI model to see if they can predict the onset of five major diseases in adults 30–65 by combining medical records with biospecimens and lifestyle data.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 30 Years to 65 Years |
| Sex | All |
| Enrollment | 1000 (estimated) |
| Sponsor | Asan Medical Center Academic / other |
| Locations | 1 site (Seoul, Seoul Special City) |
| Status | Recruiting |
| Started | April 2, 2026 |
| Main results expected | October 31, 2026 |
| Study ends | December 31, 2026 |
| Registry record updated | September 24, 2026 |
| Trial ID | NCT07595718 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults aged 30–65 with one of the specified conditions (type 2 diabetes, breast cancer, cardiovascular disease, osteoarthritis, or low back pain) or healthy controls.
✕Probably not a fit
Participants without meaningful signals in the integrated data or those not at elevated risk may see no personal benefit from the model.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study develops and validates an AI-based predictive model to estimate the risk of incident cardiovascular disease, type 2 diabetes, breast cancer, low back pain, and osteoarthritis in adults aged 30 to 65. It uses a hybrid design that blends retrospective electronic medical records and health data with prospectively collected biospecimen, omics, questionnaire, and digital health information. Data are drawn from about 1,000 participants, including roughly 700 disease-group individuals and healthy controls, with incident status determined by EMR review up to 10 years after an index date. Prospective procedures are brief, aimed at enriching the dataset without long-term follow-up obligations. The study focuses on integrating multimodal data to enhance early risk stratification for these conditions.
Why it matters
Potential benefit: If successful, the model could help clinicians identify high-risk individuals earlier and personalize prevention strategies.
How similar studies have gone: Prior research suggests AI-based risk prediction with multimodal data can improve accuracy, but application to this specific set of diseases in this age range is still evolving.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Adults aged 30 to 65 years. 2. Disease group: Participants with a confirmed diagnosis of at least one of the following conditions: type 2 diabetes mellitus, breast cancer, cardiovascular disease, osteoarthritis, or low back pain. 3. Healthy control group: Participants with no prior diagnosis of type 2 diabetes mellitus, breast cancer, cardiovascular disease, osteoarthritis, or low back pain. 4. No history or current diagnosis of major medical conditions that may affect study outcomes, including but not limited to chronic kidney disease or liver cirrhosis. 5. Ability to understand the study procedures and provision of written informed consent prior to participation. Exclusion Criteria: 1. Participants with incomplete or insufficient clinical or health screening data. 2. Participants considered inappropriate for study participation by the investigator.
Where it's running
-
Seoul Asan Medical Center
Seoul, Seoul Special City, South Korea Recruiting
Study contacts
- Study coordinator: Jaeyong Jeon
- Email: jyjeon71@gmail.com
- Phone: +82-2-3010-3791
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.