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Volume 10 Supplement 1

HealTAC-2018: Unlocking Evidence Contained in Healthcare Free-text


Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. The Supplement Editors declare that they have no competing interests.

Manchester, UK18-19 April 2018

Edited by Goran Nenadic

Conference website

  1. With the improvements to text mining technology and the availability of large unstructured Electronic Healthcare Records (EHR) datasets, it is now possible to extract structured information from raw text conta...

    Authors: Beatrice Alex, Claire Grover, Richard Tobin, Cathie Sudlow, Grant Mair and William Whiteley
    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):23
  2. Deep Learning opens up opportunities for routinely scanning large bodies of biomedical literature and clinical narratives to represent the meaning of biomedical and clinical terms. However, the validation and ...

    Authors: Mercedes Arguello-Casteleiro, Robert Stevens, Julio Des-Diz, Chris Wroe, Maria Jesus Fernandez-Prieto, Nava Maroto, Diego Maseda-Fernandez, George Demetriou, Simon Peters, Peter-John M. Noble, Phil H. Jones, Jo Dukes-McEwan, Alan D. Radford, John Keane and Goran Nenadic
    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):22
  3. Significant amounts of health data are stored as free-text within clinical reports, letters, discharge summaries and notes. Busy clinicians have limited time to read such large amounts of free-text and are at ...

    Authors: Alicja Piotrkowicz, Owen Johnson and Geoff Hall
    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):21
  4. Free text in electronic health records (EHR) may contain additional phenotypic information beyond structured (coded) information. For major health events – heart attack and death – there is a lack of studies e...

    Authors: Anoop D. Shah, Emily Bailey, Tim Williams, Spiros Denaxas, Richard Dobson and Harry Hemingway
    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):20
  5. There is an increasing amount of unstructured medical data that can be analysed for different purposes. However, information extraction from free text data may be particularly inefficient in the presence of sp...

    Authors: Hegler Tissot and Richard Dobson
    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):17

Annual Journal Metrics

  • 2022 Citation Impact
    1.9 - 2-year Impact Factor
    2.6 - 5-year Impact Factor
    0.870 - SNIP (Source Normalized Impact per Paper)
    0.697 - SJR (SCImago Journal Rank)

    2023 Speed
    23 days submission to first editorial decision for all manuscripts (Median)
    265 days submission to accept (Median)

    2023 Usage 
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