AI-Based Phenome Data Analysis for Predicting the Onset of Major Diseases

Recruiting now

Conditions studied: Diabetes Mellitus Type 2, Breast Neoplasms, Low Back Pain, Osteoarthritis, Cardiovascular Diseases

In brief

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 60 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.

Key facts

Study ID
NCT07595718
Run by
Jae Yong Jeon, MD
People needed
1000
Starts
2026-04-02
Expected to finish
2026-12-31
Last updated by the study team
2026-05-19

Who can join

Age: 30 and older, up to 60. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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