Why we need a small data paradigm

Background There is great interest in and excitement about the concept of personalized or precision medicine and, in particular, advancing this vision via various ‘big data’ efforts. While these methods are necessary, they are insufficient to achieve the full personalized medicine promise. A rigorou...

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Veröffentlicht in:	BMC medicine Jg. 17; H. 1; S. 133 - 9
Hauptverfasser:	Hekler, Eric B., Klasnja, Predrag, Chevance, Guillaume, Golaszewski, Natalie M., Lewis, Dana, Sim, Ida
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 17.07.2019 BioMed Central Ltd BMC
Schlagworte:	Analysis Artificial intelligence Beyond Big Data to new Biomedical and Health Data Science: moving to next century precision health Big data Biomedicine Cellular proteins Chronic diseases Computer Science Cooperative Behavior Data Interpretation, Statistical Data science Data Science - methods Data Science - trends Datasets as Topic - standards Datasets as Topic - statistics & numerical data Datasets as Topic - supply & distribution Debate Delivery of Health Care - methods Delivery of Health Care - statistics & numerical data Ecology, environment Electronic records Emerging Technologies Evidence-based medicine Health Health care reform High-Throughput Screening Assays - methods High-Throughput Screening Assays - statistics & numerical data Humans Learning Life Sciences Management Medical informatics Medical records Medicine Medicine & Public Health Personalized medicine Precision health Precision medicine Precision Medicine - methods Precision Medicine - statistics & numerical data Santé publique et épidémiologie Small data Small-Area Analysis United States Small data Data science Precision medicine Personalized medicine Artificial intelligence Precision health
ISSN:	1741-7015, 1741-7015
Online-Zugang:	Volltext
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