scholarly journals Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Riccardo Miotto ◽  
Li Li ◽  
Brian A. Kidd ◽  
Joel T. Dudley
2021 ◽  
Author(s):  
Carlos Molina ◽  
Belén Prados-Suarez

In this paper we propose a new definition of digital phenotype to enrich the formulation with information stored in the Electronic Health Records (EHR) plus data obtained using wearables. On this basis, we describe how to use this formalism to represent the health state of a patient in a given moment (retrospective, present, or future) and how can it be applied for personalized medicine to find out the mutations that should be introduced at present to reach a better health status in the future.


Nature ◽  
2019 ◽  
Vol 573 (7775) ◽  
pp. S114-S116 ◽  
Author(s):  
Jeff Hecht

Author(s):  
Nicola T. Shaw

AbstractThis review attempts to address the question: is the Electronic Medical Record (EMR) our best friend or sworn enemy in the context of Clinical Governance and Laboratory Medicine? It provides a brief overview of the history and development of Clinical Governance before going on to define an EMR. It considers how EMRs could assist in delivering quality care in laboratory medicine. A number of outstanding issues regarding EMRs and electronic health records (EHRs) are identified and discussed briefly before the author provides a brief outlook on the future of clinical governance and EMRs in laboratory medicine.


2018 ◽  
Vol 378 (21) ◽  
pp. 1960-1962 ◽  
Author(s):  
Katherine Choi ◽  
Yevgeniy Gitelman ◽  
David A. Asch

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