Published on in Vol 4, No 2 (2018): CHC18

Prospective Real-World Performance Evaluation of a Machine Learning Algorithm to Predict 30-Day Readmissions in Patients with Heart Failure Using Electronic Medical Record Data

Prospective Real-World Performance Evaluation of a Machine Learning Algorithm to Predict 30-Day Readmissions in Patients with Heart Failure Using Electronic Medical Record Data

Prospective Real-World Performance Evaluation of a Machine Learning Algorithm to Predict 30-Day Readmissions in Patients with Heart Failure Using Electronic Medical Record Data

Sujay S Kakarmath 1, 2, 3*, MBBS, MS;  Neda Derakhshani 2*, MSc;  Sara B. Golas 2*, MA;  Jennifer Felsted 2, 4*, PhD;  Takuma Shibahara 5*, PhD;  Hideo Aoki 5*;  Mika Takata 6*;  Ken Naono 5*, PhD;  Joseph Kvedar 2, 4, 7*, MD;  Kamal Jethwani 2, 4, 7*, MD, MPH;  Stephen Agboola 2, 4, 7*, MD, MPH

1 Harvard Medical School , Bostonn, MA, US

2 Connected Health Innovation , Partners HealthCare, Boston, MA, US

3 Massachusetts General Hospital , Boston, MA, US

4 Harvard Medical School , Boston, MA, US

5 Research and Development Group , Hitachi, Ltd, Tokyo , JP

6 Big Data Laboratory , Hitachi America Ltd, Santa Clara, CA, US

7 Massachusetts General Hospital , Boston, MA, US

*all authors contributed equally

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