About: Big data analytics for preventive medicine

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Big data analytics for preventive medicine
Creator	Xu, • Imran, • Razzak, Muhammad
source	Medline; PMC
abstract	Medical data is one of the most rewarding and yet most complicated data to analyze. How can healthcare providers use modern data analytics tools and technologies to analyze and create value from complex data? Data analytics, with its promise to efficiently discover valuable pattern by analyzing large amount of unstructured, heterogeneous, non-standard and incomplete healthcare data. It does not only forecast but also helps in decision making and is increasingly noticed as breakthrough in ongoing advancement with the goal is to improve the quality of patient care and reduces the healthcare cost. The aim of this study is to provide a comprehensive and structured overview of extensive research on the advancement of data analytics methods for disease prevention. This review first introduces disease prevention and its challenges followed by traditional prevention methodologies. We summarize state-of-the-art data analytics algorithms used for classification of disease, clustering (unusually high incidence of a particular disease), anomalies detection (detection of disease) and association as well as their respective advantages, drawbacks and guidelines for selection of specific model followed by discussion on recent development and successful application of disease prevention methods. The article concludes with open research challenges and recommendations.
has issue date	2019-03-16(xsd:dateTime)
bibo:doi	10.1007/s00521-019-04095-y
bibo:pmid	32205918
has license	no-cc
sha1sum (hex)	ac89bccb5806eeafc6122a7e27affea4fe8cb809
schema:url	https://doi.org/10.1007/s00521-019-04095-y
resource representing a document's title	Big data analytics for preventive medicine
has PubMed Central identifier	PMC7088441
has PubMed identifier	32205918
schema:publication	Neural Comput Appl
resource representing a document's body	covid:ac89bccb5806eeafc6122a7e27affea4fe8cb809#body_text
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