Machine Learning for Identification of Future Disease Development: A Nationwide Cohort Study (MILESTONE)
NCT ID: NCT02931500
Last Updated: 2018-01-10
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
510000 participants
OBSERVATIONAL
2016-07-01
2018-12-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
RETROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
ALL
No
Sponsors
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Yonsei University
OTHER
Responsible Party
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Hyuk-Jae Chang
Professor
Principal Investigators
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Hyuk-Jae Chang, PhD
Role: PRINCIPAL_INVESTIGATOR
Yonsei Univerity
Locations
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Yonsei University Severance Hospital
Seoul, , South Korea
Countries
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Central Contacts
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Facility Contacts
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References
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Cho IJ, Sung JM, Kim HC, Lee SE, Chae MH, Kavousi M, Rueda-Ochoa OL, Ikram MA, Franco OH, Min JK, Chang HJ. Development and External Validation of a Deep Learning Algorithm for Prognostication of Cardiovascular Outcomes. Korean Circ J. 2020 Jan;50(1):72-84. doi: 10.4070/kcj.2019.0105. Epub 2019 Aug 19.
Cho IJ, Sung JM, Chang HJ, Chung N, Kim HC. Incremental Value of Repeated Risk Factor Measurements for Cardiovascular Disease Prediction in Middle-Aged Korean Adults: Results From the NHIS-HEALS (National Health Insurance System-National Health Screening Cohort). Circ Cardiovasc Qual Outcomes. 2017 Nov;10(11):e004197. doi: 10.1161/CIRCOUTCOMES.117.004197.
Other Identifiers
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4-2016-0383
Identifier Type: -
Identifier Source: org_study_id
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