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

Conditions studied

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

About this study

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.

Primary outcomes

• Number of Participants With Incident Target Disease or Condition Identified Up to 10 Years After the Index Date (Up to 10 years after the index date)

Eligibility information

Study locations

• Seoul Asan Medical Center, Seoul, Seoul Special City 05505 South Korea