Using syndrome mining with the Health and Retirement Study to identify the deadliest and least deadly frailty syndromes

@article{Chao2020UsingSM,
  title={Using syndrome mining with the Health and Retirement Study to identify the deadliest and least deadly frailty syndromes},
  author={Y. Chao and Chao-Jung Wu and Hsing-Chien Wu and Hui-Ting Hsu and Lien-Cheng Tsao and Yen-Po Cheng and Yi-Chun Lai and Wei-Chih Chen},
  journal={Scientific Reports},
  year={2020},
  volume={10}
}
Syndromes are defined with signs or symptoms that occur together and represent conditions. We use a data-driven approach to identify the deadliest and most death-averse frailty syndromes based on frailty symptoms. A list of 72 frailty symptoms was retrieved based on three frailty indices. We used data from the Health and Retirement Study (HRS), a longitudinal study following Americans aged 50 years and over. Principal component (PC)-based syndromes were derived based on a principal component… Expand
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