A kernel-based framework for medical big-data analytics
Book chapter
Windridge, D. and Bober, M. 2014. A kernel-based framework for medical big-data analytics. in: Interactive Knowledge Discovery and Data Mining in Biomedical Informatics: State-of-the-Art and Future Challenges Springer.
Chapter title | A kernel-based framework for medical big-data analytics |
---|---|
Authors | Windridge, D. and Bober, M. |
Abstract | The recent trend towards standardization of Electronic Health Records (EHRs) represents a significant opportunity and challenge for medical big-data analytics. The challenge typically arises from the nature of the data which may be heterogeneous, sparse, very high-dimensional, incomplete and inaccurate. Of these, standard pattern recognition methods can typically address issues of high-dimensionality, sparsity and inaccuracy. The remaining issues of incompleteness and heterogeneity however are problematic; data can be as diverse as handwritten notes, blood-pressure readings and MR scans, and typically very little of this data will be co-present for each patient at any given time interval. |
Language | English |
Book title | Interactive Knowledge Discovery and Data Mining in Biomedical Informatics: State-of-the-Art and Future Challenges |
Publisher | Springer |
Series | Lecture Notes in Computer Science |
ISBN | |
Hardcover | 9783662439678 |
ISSN | 0302-9743 |
Publication dates | |
08 Oct 2014 | |
Publication process dates | |
Deposited | 22 Apr 2016 |
Accepted | 07 May 2014 |
Output status | Published |
Accepted author manuscript | |
Copyright Statement | The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-662-43968-5_11 |
Additional information | Series ISSN: 0302-9743 |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-662-43968-5_11 |
Journal | Interactive Knowledge Discovery and Data Mining in Biomedical Informatics |
https://repository.mdx.ac.uk/item/864q2
Download files
36
total views2
total downloads2
views this month0
downloads this month