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    Timeline and episode-structured clinical data: pre-processing for Data Mining and analytics

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    Authors
    Lu, Jing
    Hales, Alan
    Rew, David
    Keech, Malcolm
    Affiliation
    Southampton Solent University
    University Hospital Southampton
    University of Bedfordshire
    Issue Date
    2016-06-23
    Subjects
    pre-processing
    breast cancer data
    electronic patient records
    data mining
    health informatics
    
    Metadata
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    Abstract
    Data Mining has been used in the healthcare domain for diagnosis and treatment analysis, resource management and fraud detection. It brings a set of tools and techniques that can be applied to large-scale patient data to discover underlying patterns and provide healthcare professionals an additional source of knowledge for making decisions. The Southampton Breast Cancer Data System (SBCDS) containing some 16,000 timeline-structured records is a visually rich and highly intuitive system for the manual and automated transfer of demographic, pathology and treatment data into an episode-based structure. While expansion of the data mining capability in SBCDS is one of the objectives of our research, real-world patient data is generally incomplete, inconsistent and containing errors. This case study will focus on the data pre-processing stage in order to clean the raw data and prepare the final dataset for use in data mining and analytics. Some initial results are given for sequential patterns mining and classification which highlight the advantages of the approach.
    Citation
    Lu J, Hales A, Rew D, Keech M (2016) 'Timeline and episode-structured clinical data: pre-processing for Data Mining and analytics', IEEE 32nd International Conference on Data Engineering Workshops (ICDEW) - Helsinki, Institute of Electrical and Electronics Engineers Inc..
    Publisher
    Institute of Electrical and Electronics Engineers Inc.
    URI
    http://hdl.handle.net/10547/624499
    DOI
    10.1109/ICDEW.2016.7495618
    Additional Links
    https://ieeexplore.ieee.org/document/7495618
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    9781509021086
    ae974a485f413a2113503eed53cd6c53
    10.1109/ICDEW.2016.7495618
    Scopus Count
    Collections
    Computing

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