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Development and External Validation of a Deep Learning Algorithm for Prognostication of Cardiovascular Outcomes

Title
Development and External Validation of a Deep Learning Algorithm for Prognostication of Cardiovascular Outcomes
Authors
Cho, In-JeongSung, Ji MinKim, Hyeon ChangLee, Sang-EunChae, Myeong-HunKavousi, MaryamRueda-Ochoa, Oscar L.Ikram, M. ArfanFranco, Oscar H.Min, James K.Chang, Hyuk-Jae
Ewha Authors
조인정
Issue Date
2020
Journal Title
KOREAN CIRCULATION JOURNAL
ISSN
1738-5520JCR Link

1738-5555JCR Link
Citation
KOREAN CIRCULATION JOURNAL vol. 50, no. 1, pp. 72 - 84
Keywords
Cardiovascular diseasesArtificial intelligence
Publisher
KOREAN SOC CARDIOLOGY
Indexed
SCIE; SCOPUS; KCI WOS scopus
Document Type
Article
Abstract
Background and Objectives: We aim to explore the additional discriminative accuracy of a deep learning (DL) algorithm using repeated-measures data for identifying people at high risk for cardiovascular disease (CVD), compared to Cox hazard regression. Methods: Two CVD prediction models were developed from National Health Insurance Service-Health Screening Cohort (NHIS-HEALS): a Cox regression model and a DL model. Performance of each model was assessed in the internal and 2 external validation cohorts in Koreans (National Health Insurance Service-National Sample Cohort; NHIS-NSC) and in Europeans (Rotterdam Study). A total of 412,030 adults in the NHIS-HEALS; 178,875 adults in the NHIS-NSC; and the 4,296 adults in Rotterdam Study were included. Results: Mean ages was 52 years (46% women) and there were 25,777 events (6.3%) in NHIS-HEALS during the follow-up. In internal validation, the DL approach demonstrated a C-statistic of 0.896 (95% confidence interval, 0.886-0.907) in men and 0.921 (0.908-0.934) in women and improved reclassification compared with Cox regression (net reclassification index [NM], 24.8% in men, 29.0% in women). In external validation with NHIS-NSC, DL demonstrated a C-statistic of 0.868 (0.860-0.876) in men and 0.889 (0.876-0.898) in women, and improved reclassification compared with Cox regression (NRI, 24.9% in men, 26.2% in women). In external validation applied to the Rotterdam Study, DL demonstrated a C-statistic of 0.860 (0.824-0.897) in men and 0.867 (0.830-0.903) in women, and improved reclassification compared with Cox regression (NRI, 36.9% in men, 31.8% in women). Conclusions: A DL algorithm exhibited greater discriminative accuracy than Cox model approaches.
DOI
10.4070/kcj.2019.0105
Appears in Collections:
의료원 > 의료원 > Journal papers
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