Cardiovascular Risk & Heart Failure Cohort (10,000 Patients, 10-Year Follow-Up)

This upload contains the full technical documentation and a free evaluation sample (500 patients, 4,210 annual visit records) — not the full dataset. The complete dataset — 10,000 patients, 77,164 annual visit records, up to 10 years of follow-up — is available at: https://sentineldata.com.ua/dataset/cardiovascular-risk-heart-failure-cohort Sample contents: sample_patients.parquet 500 rows sample_visits.parquet 4,210 rows sample_outcomes.parquet 500 rows sample_true_state.parquet 500 rows CSV mirrors of every sample table are included, plus a short guide on opening Parquet files. The sample is the first 500 patients by ID (CARD-00001–CARD-00500), all from the primary-prevention stratum — it does not include secondary-prevention or heart-failure patients. Both of those strata, and the full 10-year outcome history, are only in the complete dataset linked above. Fully synthetic. Contains no real patient data. Every generative parameter is traceable to a published, verified source. 1. Overview Cardiovascular Risk & Heart Failure Cohort is a fully synthetic, longitudinal cohort of 10,000 patients followed for up to 10 years (77,164 annual visit records), built for cardiovascular risk-prediction modeling, heart-failure research, and synthetic-control / methods-development work. Baseline risk is driven by SCORE2 / SCORE2-OP (ESC 2021) and the ASCVD Pooled Cohort Equations (ACC/AHA ... Full description with all tables is on the Wiki page of this project. Full dataset and purchase: https://sentineldata.com.ua/dataset/cardiovascular-risk-heart-failure-cohort . Zenodo copy: https://doi.org/10.5281/zenodo.22996512

Authors

Publication Details

Journal
Open Science Framework
Published
2026-11-07
DOI
https://doi.org/10.17605/osf.io/2dy6k
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
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article

Cardiovascular Risk & Heart Failure Cohort (10,000 Patients, 10-Year Follow-Up)

Chekerskyi Maksym
4 links
Open Science Framework
Artificial Intelligence in Healthcare
article

Cardiovascular Risk & Heart Failure Cohort (10,000 Patients, 10-Year Follow-Up)

Chekerskyi Maksym
article en

Abstract

This upload contains the full technical documentation and a free evaluation sample (500 patients, 4,210 annual visit records) — not the full dataset. The complete dataset — 10,000 patients, 77,164 annual visit records, up to 10 years of follow-up — is available at: https://sentineldata.com.ua/dataset/cardiovascular-risk-heart-failure-cohort Sample contents: sample_patients.parquet 500 rows sample_visits.parquet 4,210 rows sample_outcomes.parquet 500 rows sample_true_state.parquet 500 rows CSV mirrors of every sample table are included, plus a short guide on opening Parquet files. The sample is the first 500 patients by ID (CARD-00001–CARD-00500), all from the primary-prevention stratum — it does not include secondary-prevention or heart-failure patients. Both of those strata, and the full 10-year outcome history, are only in the complete dataset linked above. Fully synthetic. Contains no real patient data. Every generative parameter is traceable to a published, verified source. 1. Overview Cardiovascular Risk & Heart Failure Cohort is a fully synthetic, longitudinal cohort of 10,000 patients followed for up to 10 years (77,164 annual visit records), built for cardiovascular risk-prediction modeling, heart-failure research, and synthetic-control / methods-development work. Baseline risk is driven by SCORE2 / SCORE2-OP (ESC 2021) and the ASCVD Pooled Cohort Equations (ACC/AHA ... Full description with all tables is on the Wiki page of this project. Full dataset and purchase: https://sentineldata.com.ua/dataset/cardiovascular-risk-heart-failure-cohort . Zenodo copy: https://doi.org/10.5281/zenodo.22996512

Open Science Framework
Good health and well-being
Openalex Percentile: Top 12%
Artificial Intelligence in Healthcare
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Cardiovascular Risk & Heart Failure Cohort (10,000 Patients, 10-Year Follow-Up) — Chekerskyi Maksym · Open Science Framework (2026) | TGRS Research Map | TGRS