Text mining MEDLINE to support public health

Pita Costa, João; Stopar, Luka; Fuart, Flavio; Grobelnik, Marko; Santanam, Raghu; Sun, Chenlu; Carlin, Paul; Black, Michaela and Wallace, Jonathan (2018). Text mining MEDLINE to support public health. In: SiKDD 2018: Conference on Data Mining and Data Warehouses, 11 Oct 2018, Ljubljana.

URL: https://ailab.ijs.si/dunja/SiKDD2018/Papers/PitaCo...

Abstract

Today’s society is data rich and information driven, with access to numerous data sources available that have the potential to provide new insights into areas such as disease prevention, personalised medicine and data driven policy decisions. This paper describes and demonstrates the use of text mining tools developed to support public health institutions to complement their data with other accessible open data sources, optimize analysis and gain insight when examining policy. In particular we focus on the exploration of MEDLINE, the biggest structured open dataset of biomedical knowledge. In MEDLINE we utilize its terminology for indexing and cataloguing biomedical information – MeSH – to maximize the efficacy of the dataset.

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About

• Item ORO ID
• 72250
• Item Type
• Conference or Workshop Item
• Project Funding Details

• Funded Project Name	Project ID	Funding Body
  MIDAS	727721	SC1-PM-18-2016 ‘Big Data supporting Public Health policies’:H2020

• Keywords
• big data; public health; healthcare; text mining; machine learning; MEDLINE; MeSH Headings
• Academic Unit or School
• Faculty of Wellbeing, Education and Language Studies (WELS) > Health, Wellbeing and Social Care
  Faculty of Wellbeing, Education and Language Studies (WELS)
• Copyright Holders
• © 2020 The Authors
• Related URLs
• • https://ailab.ijs.si/dunja/SiKDD2018/(Other)
• Depositing User
• Paul Carlin