Machine Learning for Identification of Future Disease Development: A Nationwide Cohort Study (MILESTONE)

Yonsei University510,000 enrolled

Overview

To develop machine learning algorithms for the identification of future development of cardiovascular and metabolic disease

The MILESTONE trial is retrospective and data review study with health checkup data from the National Health Insurance Services(NHIS) in Korea. The data will be included general health examination for individuals , type of health insurance, medical bill details, medical histories, treatment and prescriptions about 514,795 individuals who were over 40 years old.

Study Type

OBSERVATIONAL

Enrollment

510,000

Conditions

Cardiovascular Disease Metabolic Disease

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * The Subject who is got health checkup between 2002 and 2013, and had been recorded the health checkup result to the National Health Insurance Service(NHIS) in South Korea. Exclusion Criteria: * Persons whose disease development is not identified from the records due to emigration or disappearance

Locations (1)

Yonsei University Severance Hospital

Seoul, South Korea

RECRUITING

Outcomes

Primary Outcomes

Accuracy in prediction of development of cardiovascular and metabolic disease using machine learning algorithm

Time frame: 6months

Secondary Outcomes

Accuracy in prediction of development of cardiovascular and metabolic disease using logistic regression analysis

Time frame: 6months

Accuracy in prediction of development of cardiovascular and metabolic disease using Framingham risk score

Time frame: 6months

Central Contacts

Hyuk-Jae Chang, PhD

CONTACT

hjchang@yuhs.ac

In-Jeong Cho

CONTACT

injeongcho@yuhs.ac

Data from ClinicalTrials.gov

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