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Paper Details

Predicting hypertension onset from longitudinal electronic health records with deep learning.
JAMIA Open
4
2022
Hypertension, LSTM, LSTM network, Lipid disorders, aggregated features, cardiovascular diseases, chronic, chronic diseases, hypertension, patients, renal disorders, type 2 diabetes
Author NameAffiliation
Girish N NadkarniHasso Plattner Institute, University of Potsdam
Girish N NadkarniIcahn School of Medicine at Mount Sinai
Girish N NadkarniHasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai
Girish N NadkarniHasso Plattner Institute, University of Potsdam
Girish N NadkarniHasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai
Girish N NadkarniIcahn School of Medicine at Mount Sinai
Riccardo MiottoHasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai
Riccardo MiottoIcahn School of Medicine at Mount Sinai
Riccardo MiottoHasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai
Riccardo MiottoIcahn School of Medicine at Mount Sinai
Erwin P BottingerHasso Plattner Institute, University of Potsdam
Erwin P BottingerHasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai
Erwin P BottingerIcahn School of Medicine at Mount Sinai
Erwin P BottingerIcahn School of Medicine at Mount Sinai
Erwin P BottingerHasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai
Erwin P BottingerIcahn School of Medicine at Mount Sinai
Erwin P BottingerIcahn School of Medicine at Mount Sinai
Erwin P BottingerHasso Plattner Institute, University of Potsdam
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