Big data analytics in healthcare: promise and potential
Wullianallur Raghupathi,Viju Raghupathi +1 more
- Vol. 2, Iss: 1, pp 3-3
Reads0
Chats0
TLDR
Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs, and its potential is great; however there remain challenges to overcome.Abstract:
Objective: To describe the promise and potential of big data analytics in healthcare. Methods: The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. Results: The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Conclusions: Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.read more
Citations
More filters
Journal ArticleDOI
A survey towards an integration of big data analytics to big insights for value-creation
Mandeep Kaur Saggi,Sushma Jain +1 more
TL;DR: This article presents a comprehensive, well-informed examination, and realistic analysis of deploying big data analytics successfully in companies and presents a methodical analysis for the usage of Big Data Analytics in various applications such as agriculture, healthcare, cyber security, and smart city.
Journal ArticleDOI
What is precision medicine
TL;DR: This paper is to provide a more comprehensive definition of precision medicine that incorporates the derivation of novel taxonomies and their role in healthcare as part of the cycle, but also covers related terms.
Journal ArticleDOI
Open challenges for data stream mining research
Georg Krempl,Indre Žliobaite,Dariusz Brzezinski,Eyke Hüllermeier,Vincent Lemaire,Tino Noack,Ammar Shaker,Sonja Sievi,Myra Spiliopoulou,Jerzy Stefanowski +9 more
TL;DR: This article presents a discussion on eight open challenges for data stream mining, which cover the full cycle of knowledge discovery and involve such problems as protecting data privacy, dealing with legacy systems, handling incomplete and delayed information, analysis of complex data, and evaluation of stream mining algorithms.
Journal ArticleDOI
Wearable sensors for monitoring the physiological and biochemical profile of the athlete
Dhruv R. Seshadri,Ryan T. Li,James E. Voos,James R. Rowbottom,Celeste M. Alfes,Christian A. Zorman,Colin K. Drummond +6 more
TL;DR: The emergence of flexible and stretchable electronics coupled with the ability to quantify biochemical analytes and physiological parameters have enabled the detection of key markers indicative of performance and stress, as reviewed in this paper.
Journal ArticleDOI
A Survey on Big Data Market: Pricing, Trading and Protection
TL;DR: This paper study a variety of data pricing models, categorize them into different groups, and conduct a comprehensive comparison of the pros and cons of these models, and focuses on the design of data trading platforms and schemes, supporting efficient, secure, and privacy-preserving data trading.
References
More filters
Book
Big data: The next frontier for innovation, competition, and productivity
TL;DR: The amount of data in the authors' world has been exploding, and analyzing large data sets will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey.
Book
Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data
Paul Zikopoulos,Chris Eaton +1 more
TL;DR: This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform.
Proceedings ArticleDOI
Big Data analytics
TL;DR: This analysis illustrates that the Big Data analytics is a fast-growing, influential practice and a key enabler for the social business and is critical for success in the age of social media.
Proceedings ArticleDOI
Towards large-scale twitter mining for drug-related adverse events
TL;DR: An approach to find drug users and potential adverse events by analyzing the content of twitter messages utilizing Natural Language Processing (NLP) and to build Support Vector Machine (SVM) classifiers is described, suggesting that daily-life social networking data could help early detection of important patient safety issues.
Book
Big Data Analytics: Turning Big Data into Big Money
TL;DR: Ohlhorst et al. as mentioned in this paper focused on the business and financial value of big data analytics and discussed how to turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportunities.