Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures

no code implementations • 27 Jul 2023 • Yuanfang Ren, Yanjun Li, Tyler J. Loftus, Jeremy Balch, Kenneth L. Abbott, Shounak Datta, Matthew M. Ruppert, Ziyuan Guan, Benjamin Shickel, Parisa Rashidi, Tezcan Ozrazgat-Baslanti, Azra Bihorac

With clustering analysis for vital signs within six hours of admission, patient phenotypes with distinct pathophysiological signatures and outcomes may support early clinical decisions.

Clustering

Computable Phenotypes of Patient Acuity in the Intensive Care Unit

no code implementations • 27 Apr 2020 • Yuanfang Ren, Jeremy Balch, Kenneth L. Abbott, Tyler J. Loftus, Benjamin Shickel, Parisa Rashidi, Azra Bihorac, Tezcan Ozrazgat-Baslanti

We gathered two single-center, longitudinal electronic health record datasets for 51, 372 adult ICU patients admitted to the University of Florida Health (UFH) Gainesville (GNV) and Jacksonville (JAX).

Decision Making