AI-Based Phenome Data Analysis for Predicting the Onset of Major Diseases
Key facts
- Where
- Seoul, South KoreaSee the site
Could this be for you?
Answer for yourself. This is not a decision: only the study team can say whether you can take part.
- Are you between 30 and 65 years old?
Source: NCT07595718, who can take part
Where in South Korea
- Seoul ASAN Medical CenterSeoul, South KoreaTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Jae Yong Jeon, MD
- Trial code
- NCT07595718
- Record updated
- 24 September 2026
- Original description
This study aims to develop and validate an artificial intelligence (AI)-based predictive model to estimate the risk of incident onset of five major diseases or conditions: cardiovascular disease, type 2 diabetes mellitus, breast cancer, low back pain, and osteoarthritis, in adults aged 30 to 65 years.Read full original descriptionShow less
This study aims to develop and validate an artificial intelligence (AI)-based predictive model to estimate the risk of incident onset of five major diseases or conditions: cardiovascular disease, type 2 diabetes mellitus, breast cancer, low back pain, and osteoarthritis, in adults aged 30 to 65 years.
For each participant, an index date will be defined as the date of a prior health screening or another protocol-defined baseline clinical date. Incident disease status for each target disease or condition will be ascertained by retrospective review of electronic medical records for up to 10 years after the index date.
The study integrates retrospective clinical, health screening, laboratory, imaging, and electronic medical record data with prospectively collected biospecimen, proteomic, genomic, questionnaire, lifestyle, and digital health data. Prospective study procedures will be completed over approximately 1 week, with up to 2 additional weeks if needed.
By combining multimodal data, this study seeks to improve disease risk prediction and to identify clinical and biological factors associated with disease onset, ultimately supporting personalized risk stratification and preventive healthcare strategies.
Inclusion: Adults aged 30 to 65 years; 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; Healthy control group: Participants with no prior diagnosis of type 2 diabetes mellitus, breast cancer, cardiovascular disease, osteoarthritis, or low back pain; 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; Ability to understand the study procedures and provision of written informed consent prior to participation.
Exclusion: Participants with incomplete or insufficient clinical or health screening data; Participants considered inappropriate for study participation by the investigator.