Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Arlene Casey"'
Autor:
Katherine O'Sullivan, Milan Markovic, Jaroslaw Dymiter, Adrian Martin, Chinasa Odo, Helen Rowlands, Ana Ciocarlan, Katie Wilde, Arlene Casey
Publikováno v:
International Journal of Population Data Science, Vol 9, Iss 5 (2024)
We present a prototype solution for improving transparency and quality assurance of the data linkage process through a data provenance dashboard designed to assist data analysts, researchers and information governance teams in authenticating and audi
Externí odkaz:
https://doaj.org/article/4455002f468c4f8fa0452f77b7c477f7
Publikováno v:
International Journal of Population Data Science, Vol 9, Iss 5 (2024)
Objective and Approach Many people do not respond to antidepressants and our poor mechanistic understanding of antidepressant response has hampered efforts to personalise treatment. Understanding how and when antidepressants work at an individual lev
Externí odkaz:
https://doaj.org/article/8785a088b0894c0988b64c660f2a6914
Autor:
Hang Dong, Víctor Suárez-Paniagua, Huayu Zhang, Minhong Wang, Arlene Casey, Emma Davidson, Jiaoyan Chen, Beatrice Alex, William Whiteley, Honghan Wu
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-17 (2023)
Abstract Background Computational text phenotyping is the practice of identifying patients with certain disorders and traits from clinical notes. Rare diseases are challenging to be identified due to few cases available for machine learning and the n
Externí odkaz:
https://doaj.org/article/ddad622df8154c81a37d192f7e613ad8
Autor:
Huayu Zhang, Arlene Casey, Imane Guellil, Víctor Suárez-Paniagua, Clare MacRae, Charis Marwick, Honghan Wu, Bruce Guthrie, Beatrice Alex
Publikováno v:
Frontiers in Digital Health, Vol 5 (2023)
IntroductionLinking free-text addresses to unique identifiers in a structural address database [the Ordnance Survey unique property reference number (UPRN) in the United Kingdom (UK)] is a necessary step for downstream geospatial analysis in many dig
Externí odkaz:
https://doaj.org/article/ec156d78d3dd4bb4a92ddb4f86703ffe
Autor:
Arlene Casey, Emma Davidson, Claire Grover, Richard Tobin, Andreas Grivas, Huayu Zhang, Patrick Schrempf, Alison Q. O’Neil, Liam Lee, Michael Walsh, Freya Pellie, Karen Ferguson, Vera Cvoro, Honghan Wu, Heather Whalley, Grant Mair, William Whiteley, Beatrice Alex
Publikováno v:
Frontiers in Digital Health, Vol 5 (2023)
BackgroundNatural language processing (NLP) has the potential to automate the reading of radiology reports, but there is a need to demonstrate that NLP methods are adaptable and reliable for use in real-world clinical applications.MethodsWe tested th
Externí odkaz:
https://doaj.org/article/0c251b629e384478bfd162bf6dd1e303
Autor:
Emma M. Davidson, Michael T. C. Poon, Arlene Casey, Andreas Grivas, Daniel Duma, Hang Dong, Víctor Suárez-Paniagua, Claire Grover, Richard Tobin, Heather Whalley, Honghan Wu, Beatrice Alex, William Whiteley
Publikováno v:
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-13 (2021)
Abstract Background Automated language analysis of radiology reports using natural language processing (NLP) can provide valuable information on patients’ health and disease. With its rapid development, NLP studies should have transparent methodolo
Externí odkaz:
https://doaj.org/article/1e2f53d1f3f843d18b45553061012a08
Autor:
Arlene Casey, Emma Davidson, Michael Poon, Hang Dong, Daniel Duma, Andreas Grivas, Claire Grover, Víctor Suárez-Paniagua, Richard Tobin, William Whiteley, Honghan Wu, Beatrice Alex
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-18 (2021)
Abstract Background Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to rad
Externí odkaz:
https://doaj.org/article/e036d2c744224b308bdf55a306a7d12b
Autor:
Arlene Casey, Mike Bennett, Richard Tobin, Claire Grover, Iona Walker, Lukas Engelmann, Beatrice Alex
Publikováno v:
Journal of Data Mining and Digital Humanities, Vol HistoInformatics, Iss HistoInformatics (2021)
The design of models that govern diseases in population is commonly built on information and data gathered from past outbreaks. However, epidemic outbreaks are never captured in statistical data alone but are communicated by narratives, supported by
Externí odkaz:
https://doaj.org/article/d0cbcfe5a58a45c889cb43fe8036aa8b
Autor:
Emma M Davidson, Arlene Casey, Claire Grover, Beatrice Alex, Honghan Wu, Archie Campbell, Fionna Chalmers, Mark Adams, Matthew Iveson, Andrew M McIntosh, Emily Ball, Kristiina Rannikmae, Heather Whalley, William N Whiteley
BackgroundCoded healthcare data may not capture all stroke cases and has limited accuracy for stroke subtypes. We sought to determine the incremental value of adding natural language processing (NLP) of free-text radiology reports to international cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb4923e9a7aeceaf67d18fdf95d8794f
https://doi.org/10.1101/2023.04.03.23288096
https://doi.org/10.1101/2023.04.03.23288096
Autor:
Arlene Casey, Claire Grover, Andreas Grivas, Víctor Suárez-Paniagua, Beatrice Alex, Daniel Duma, Honghan Wu, Heather C. Whalley, Hang Dong, William Whiteley, Emma Davidson, Richard Tobin, Michael T C Poon
Publikováno v:
Davidson, E, Poon, M, Casey, A, Grivas, A, Duma, D, Dong, H, Suarez Paniagua, V, Grover, C, Tobin, RICHARD, Whalley, H, Wu, H, Alex, B & Whiteley, W N 2021, ' The reporting quality of natural language processing studies-systematic review of studies of radiology reports ', BMC medical imaging . https://doi.org/10.1186/s12880-021-00671-8
BMC Medical Imaging
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-13 (2021)
BMC Medical Imaging
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-13 (2021)
Background Automated language analysis of radiology reports using natural language processing (NLP) can provide valuable information on patients’ health and disease. With its rapid development, NLP studies should have transparent methodology to all