Learning About Machine Learning: The Promise and Pitfalls of Big Data and the Electronic Health Record.

Display options

Format

Share it on

Circ Cardiovasc Qual Outcomes. 2016 Nov;9(6):618-620. doi: 10.1161/CIRCOUTCOMES.116.003308. Epub 2016 Nov 08.

Circulation. Cardiovascular quality and outcomes

From the Division of Cardiology, Department of Medicine; Cardiovascular Research Institute; Institute for Human Genetics; and Institute for Computational Health Sciences, University of California San Francisco, and California Institute for Quantitative Biosciences (R.C.D.); and VA Health Services Research and Development Center for Clinical Management Research, VA Ann Arbor Healthcare System, MI; Michigan Center for Health Analytics and Medical Prediction (M-CHAMP), Department of Internal Medicine, University of Michigan Medical School, Ann Arbor (B.K.N.). [email protected].
From the Division of Cardiology, Department of Medicine; Cardiovascular Research Institute; Institute for Human Genetics; and Institute for Computational Health Sciences, University of California San Francisco, and California Institute for Quantitative Biosciences (R.C.D.); and VA Health Services Research and Development Center for Clinical Management Research, VA Ann Arbor Healthcare System, MI; Michigan Center for Health Analytics and Medical Prediction (M-CHAMP), Department of Internal Medicine, University of Michigan Medical School, Ann Arbor (B.K.N.).

[No abstract available.]

Keywords: Editorials; heart failure; linear models; machine learning; medicine; risk factors