TY  - GEN
AU  - Shen, Yike
AU  - Domingo-Relloso, Arce
AU  - Kupsco, Allison
AU  - Kioumourtzoglou, Marianthi-Anna
AU  - Tellez-Plaza, Maria
AU  - Umans, Jason G
AU  - Fretts, Amanda M
AU  - Zhang, Ying
AU  - Schnatz, Peter F
AU  - Casanova, Ramon
AU  - Martin, Lisa Warsinger
AU  - Horvath, Steve
AU  - Manson, JoAnn E
AU  - Cole, Shelley A
AU  - Wu, Haotian
AU  - Whitsel, Eric A
AU  - Baccarelli, Andrea A
AU  - Navas-Acien, Ana
AU  - Gao, Feng
PY  - 2024
DO  - 10.1093/bib/bbae479
SN  - 1467-5463
UR  - https://hdl.handle.net/20.500.12105/25433
AB  - Coronary heart disease (CHD) is one of the leading causes of mortality and morbidity in the United States. Accurate time-to-event CHD prediction models with high-dimensional DNA methylation and clinical features may assist with early prediction and...
LA  - eng
PB  - Oxford University Press
KW  - Autoencoder survival analysis
KW  - Cohort studies
KW  - Coronary heart disease
KW  - Deep learning
KW  - Epigenetics
KW  - Coronary Disease
KW  - DNA Methylation
KW  - Deep Learning
KW  - Female
KW  - Humans
KW  - Male
KW  - Middle Aged
KW  - Prospective Studies
KW  - Risk Factors
KW  - Survival Analysis
TI  - AESurv: autoencoder survival analysis for accurate early prediction of coronary heart disease
TY  - research article
ER  -