MachIne LEarning for Identification of Future Development of cardiovaScular and meTabOlic Disease: a NationwidE Time-series Cohort Study (MILESTONE)
Sponsor study identifier
observational
510,000
1 country
1
Study Start
July 1, 2016
Actual (reported)Primary Completion
October 30, 2018
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Study Completion
December 31, 2018
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
To develop machine learning algorithms for the identification of future development of cardiovascular and metabolic disease
Registry-reported information. Elapsed time and enrollment totals alone do not measure study progress or recruitment pace.
December 31, 2018
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Click on a node to explore related trials.
Dates and qualifiers reported by the registry. Estimated dates do not confirm that a milestone has occurred.
July 1, 2016
Actual (reported)July 21, 2016
Actual (reported)October 13, 2016
Actual (reported)October 30, 2018
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
December 31, 2018
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Accuracy in prediction of development of cardiovascular and metabolic disease using machine learning algorithm
6months
Accuracy in prediction of development of cardiovascular and metabolic disease using logistic regression analysis
6months
Accuracy in prediction of development of cardiovascular and metabolic disease using Framingham risk score
6months
The data which is health checkup record about 510,000 Subjects between 2002 and 2013 from National Health Insurance Service (NHIS) in South Korea.
Yonsei University Severance Hospital
Seoul, 102-752, South Korea
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.
Hyuk-Jae Chang, PhD
Yonsei Univerity
First Submitted
July 21, 2016
First Posted
October 13, 2016
Study Start
July 1, 2016
Actual (reported)Primary Completion
October 30, 2018
Estimated (date passed)Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease
Contact the study team to confirm eligibility.
This estimate has passed. The registry has not confirmed an actual date for this milestone.
Study Completion
December 31, 2018
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Last Updated
January 10, 2018
Record last verified: 2018-01
Download the complete ClinicalTrials.gov record imported by Syfrah, including fields not shown in this page. The registry may contain a newer revision.
Source: ClinicalTrials.gov.
JSON downloads include source attribution and retrieval details alongside the unchanged original record or the separately normalized values.
Source retrieved: