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Healthcare data analytics

Contributor(s): Reddy, Chandan K [Editor] | Aggarwal, Charu C [Editor].
Series: Chapman &​ Hall/​CRC data mining and knowledge discovery series. Publisher: Boca Raton CRC Press 2015Description: xxviii, 724 p.ISBN: 9781482232110.Subject(s): Data Mining | Statistics as TopicDDC classification: 610.21 Summary: The book details novel techniques for acquiring, handling, retrieving, and making best use of healthcare data. It analyzes recent developments in healthcare computing and discusses emerging technologies that can help improve the health and well-being of patients. Written by prominent researchers and experts working in the healthcare domain, the book sheds light on many of the computational challenges in the field of medical informatics. Each chapter in the book is structured as a "survey-style" article discussing the prominent research issues and the advances made on that research topic. The book is divided into three major categories: • Healthcare Data Sources and Basic Analytics - details the various healthcare data sources and analytical techniques used in the processing and analysis of such data • Advanced Data Analytics for Healthcare - covers advanced analytical methods, including clinical prediction models, temporal pattern mining methods, and visual analytics • Applications and Practical Systems for Healthcare - covers the applications of data analytics to pervasive healthcare, fraud detection, and drug discovery along with systems for medical imaging and decision support Computer scientists are usually not trained in domain-specific medical concepts, whereas medical practitioners and researchers have limited exposure to the data analytics area. The contents of this book will help to bring together these diverse communities by carefully and comprehensively discussing the most relevant contributions from each domain. (https://www.crcpress.com/Healthcare-Data-Analytics/Reddy-Aggarwal/9781482232110)
List(s) this item appears in: VR_Healthcare Analytics | Big data | Laha | VR_Data Analytics, Data Visualization and Big Data
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Books Vikram Sarabhai Library
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Non-fiction 610.21 H3 (Browse shelf) Available 190485

Table of contents:

1. An introduction to healthcare data analytics
2. Electronic health records : a survey
3. Biomedical image analysis
4. Mining of sensor data in healthcare : a survey
5. Biomedical signal analysis
6. Genomic data analysis for personalized medicine
7. Natural language processing and data mining for clinical text
8. Mining the biomedical literature
9. Social media analytics for healthcare
10. A review of clinical prediction models
11. Temporal data mining for healthcare data
12. Visual analytics for healthcare
13. Predictive models for integrating clinical and genomic data
14. Information retrieval for healthcare
15. Privacy-preserving data publishing methods in healthcare
16. Data analytics for pervasive health
17. Fraud detection in healthcare
18. Data analytics for pharmaceutical discoveries
19. Clinical decision support systems
20. Computer assisted medical image analysis systems
21. Mobile imaging and analytics for biomedical data

The book details novel techniques for acquiring, handling, retrieving, and making best use of healthcare data. It analyzes recent developments in healthcare computing and discusses emerging technologies that can help improve the health and well-being of patients.

Written by prominent researchers and experts working in the healthcare domain, the book sheds light on many of the computational challenges in the field of medical informatics. Each chapter in the book is structured as a "survey-style" article discussing the prominent research issues and the advances made on that research topic. The book is divided into three major categories:
• Healthcare Data Sources and Basic Analytics - details the various healthcare data sources and analytical techniques used in the processing and analysis of such data
• Advanced Data Analytics for Healthcare - covers advanced analytical methods, including clinical prediction models, temporal pattern mining methods, and visual analytics
• Applications and Practical Systems for Healthcare - covers the applications of data analytics to pervasive healthcare, fraud detection, and drug discovery along with systems for medical imaging and decision support
Computer scientists are usually not trained in domain-specific medical concepts, whereas medical practitioners and researchers have limited exposure to the data analytics area. The contents of this book will help to bring together these diverse communities by carefully and comprehensively discussing the most relevant contributions from each domain.

(https://www.crcpress.com/Healthcare-Data-Analytics/Reddy-Aggarwal/9781482232110)

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