Challenges in designing an online healthcare platform for personalised patient analytics

Conference paper

Poh, N., Tirunagari, S. and Windridge, D. 2014. Challenges in designing an online healthcare platform for personalised patient analytics. 2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD). Orlando, FL., USA 09 - 12 Dec 2014 IEEE. pp. 1-6 https://doi.org/10.1109/CIBD.2014.7011526
TypeConference paper
TitleChallenges in designing an online healthcare platform for personalised patient analytics
AuthorsPoh, N., Tirunagari, S. and Windridge, D.
Abstract

The growing number and size of clinical medical records (CMRs) represents new opportunities for finding meaningful patterns and patient treatment pathways while at the same time presenting a huge challenge for clinicians. Indeed, CMR repositories share many characteristics of the classical ‘big data’ problem, requiring specialised expertise for data management, extraction, and modelling. In order to help clinicians make better use of their time to process data, they will need more adequate data processing and analytical tools, beyond the capabilities offered by existing general purpose database management systems or database servers.
One modelling technique that can readily benefit from the availability of big data, yet remains relatively unexplored is personalised analytics where a model is built for each patient. In this paper, we present a strategy for designing a secure healthcare platform for personalised analytics by focusing on three aspects: (1) data representation, (2) data privacy and security, and (3) personalised analytics enabled by machine learning algorithms.

Conference2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD)
Page range1-6
Proceedings Title2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD) Proceedings
ISBN
Hardcover9781479945412
Electronic9781479945405
PublisherIEEE
Publication dates
PrintDec 2014
Online19 Jan 2015
Publication process dates
Deposited22 Apr 2016
Accepted02 Jun 2014
Output statusPublished
Accepted author manuscript
File Access Level
Open
Copyright Statement

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Digital Object Identifier (DOI)https://doi.org/10.1109/CIBD.2014.7011526
Scopus EID2-s2.0-84923247411
Web address (URL) of conference proceedingshttps://ieeexplore.ieee.org/xpl/conhome/6999016/proceeding
LanguageEnglish
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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. pp. 197-208
High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP)
Abbey, C., Hope, C., Sterr, A., Elangovan, P., Geades, N., Windridge, D., Young, K., Wells, K. and Mello-Thoms, C. 2013. High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP). SPIE Proceedings Vol. 8673. https://doi.org/10.1117/12.2007557
Looking to score: the dissociation of goal influence on eye movement and meta-attentional allocation in a complex dynamic natural scene
Taya, S., Windridge, D. and Osman, M. 2012. Looking to score: the dissociation of goal influence on eye movement and meta-attentional allocation in a complex dynamic natural scene. PLoS ONE. 7 (6). https://doi.org/10.1371/journal.pone.0039060
Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution
Poh, N., Windridge, D., Mottl, V., Tatarchuk, A. and Eliseyev, A. 2010. Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution. IEEE Transactions on Information Forensics and Security. 5 (3), pp. 461-469. https://doi.org/10.1109/TIFS.2010.2053535