课题基金 / 基金详情

Supporting Evidence-based Public Health Interventions using Text Mining

Supporting Evidence-based Public Health Interventions using Text Mining
使用文本挖掘支持循证公共卫生干预措施
批准号:
MR/L01078X/1
负责人:
Sophia Ananiadou
金额:
$83.55万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2014
资助国家:
英国
项目状态:
已结题
起止时间:
2014 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
Evidence-based public health (EBPH) reviews play a central role in public health policy, practice and guidance. Their development currently involves first searching, then screening and synthesizing evidence from the vast amount of literature. Unlike systematic reviews, EBPH reviews require dynamic and multidimensional views of relevant information from the literature, without relying on a priori research questions. As a result, EBPH reviewing is a time consuming and resource intensive process that can take more than a year to complete. Since crucial information can be difficult to locate, and indeed understand given the complex nature of EBPH problems, the multiple causes and interrelations between interventions, diseases, populations and outcomes can remain hidden. This project will address these limitations by exploring new research methods, which combine text mining and machine learning to produce novel search while screening tools for public health reviews. Text mining methods will discover automatically knowledge from unstructured data and machine learning will support the prioritisation and ranking of the extracted information into meaningful topics. The combination of text mining and machine learning methods will reduce the burden of producing public health reviews which will be completed more quickly, thus meeting policy and practice timescales and increasing their cost efficiency. They also allow more timely and reliable reviews, thus improving decision making across the health sector. The project will be informed throughout by close interaction with the Centre of Public Health at NICE , who will also carry out qualitative and quantitative evaluation based on the implementation of a novel search while screening pilot system. Evaluation will be carried out on reviews related with non-communicable diseases related with prevention of hazardous and harmful drinking and excessive alcohol consumption. Moreover, given the national and international importance of EBPH reviewing, the project has developed a multistrand pathways to impact document to engage with a variety of key EBPH stakeholders both in the UK and internationally.
期刊论文(10)
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科研奖励(0)
会议论文
DOI: --
发表时间: 2017-07
期刊: J. Mach. Learn. Res.
影响因子: --
作者: [A. Brockmeier;Tingting Mu;S. Ananiadou;J. Y. Goulermas]
通讯作者: A. Brockmeier;Tingting Mu;S. Ananiadou;J. Y. Goulermas
DOI: 10.1016/j.jbi.2016.06.001
发表时间: 2016-08
期刊: Journal of biomedical informatics
影响因子: 4.5
作者: [Hashimoto K, Kontonatsios G, Miwa M, Ananiadou S]
通讯作者: Ananiadou S
DOI: 10.1186/s13326-015-0004-6
发表时间: 2015
期刊: Journal of biomedical semantics
影响因子: 1.9
作者: [Fu X, Batista-Navarro R, Rak R, Ananiadou S]
通讯作者: Ananiadou S
DOI: 10.1371/journal.pone.0126196
发表时间: 2015
期刊: PloS one
影响因子: 3.7
作者: [Bollegala D, Kontonatsios G, Ananiadou S]
通讯作者: Ananiadou S
8
    Japan Partnering Award. Text mining and bioinformatics platforms for metabolic pathway modelling.
    • 批准号:
      BB/P025684/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $5.07万
    • 财政年份:
      2017
    • 负责人:
      Sophia Ananiadou
    • 依托单位:
    Enriching Metabolic PATHwaY models with evidence from the literature (EMPATHY)
    • 批准号:
      BB/M006891/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $75.68万
    • 财政年份:
      2015
    • 负责人:
      Sophia Ananiadou
    • 依托单位:
    Mining the History of Medicine
    • 批准号:
      AH/L00982X/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $33.31万
    • 财政年份:
      2014
    • 负责人:
      Sophia Ananiadou
    • 依托单位:
    Automated Biological Event Extraction from the Literature for Drug Discovery
    • 批准号:
      BB/G013160/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $36.76万
    • 财政年份:
      2009
    • 负责人:
      Sophia Ananiadou
    • 依托单位:
    海外基金