Text Mining the History of Medicine

Historical text archives constitute a rich and diverse source of information, which is becoming increasingly readily accessible, due to large-scale digitisation efforts. However, it can be difficult for researchers to explore and search such large volumes of data in an efficient manner. Text mining...

Full description

Saved in:
Bibliographic Details
Published in:PloS one 2016-01, Vol.11 (1), p.e0144717-e0144717
Main Authors: Thompson, Paul, Batista-Navarro, Riza Theresa, Kontonatsios, Georgios, Carter, Jacob, Toon, Elizabeth, McNaught, John, Timmermann, Carsten, Worboys, Michael, Ananiadou, Sophia
Format: Article
Language:English
Subjects:
Accessibility
Analysis
Archives
Archives & records
Bioinformatics
Causality
Computer science
Data Mining
Data processing
Dating techniques
Digitization
Disease
Drugs
History of Medicine
History, 19th Century
Keywords
Medical research
Medical services
Medicine
Queries
Query expansion
Researchers
Science history
Searching
Semantics
Studies
Texts
Tuberculosis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Historical text archives constitute a rich and diverse source of information, which is becoming increasingly readily accessible, due to large-scale digitisation efforts. However, it can be difficult for researchers to explore and search such large volumes of data in an efficient manner. Text mining (TM) methods can help, through their ability to recognise various types of semantic information automatically, e.g., instances of concepts (places, medical conditions, drugs, etc.), synonyms/variant forms of concepts, and relationships holding between concepts (which drugs are used to treat which medical conditions, etc.). TM analysis allows search systems to incorporate functionality such as automatic suggestions of synonyms of user-entered query terms, exploration of different concepts mentioned within search results or isolation of documents in which concepts are related in specific ways. However, applying TM methods to historical text can be challenging, according to differences and evolutions in vocabulary, terminology, language structure and style, compared to more modern text. In this article, we present our efforts to overcome the various challenges faced in the semantic analysis of published historical medical text dating back to the mid 19th century. Firstly, we used evidence from diverse historical medical documents from different periods to develop new resources that provide accounts of the multiple, evolving ways in which concepts, their variants and relationships amongst them may be expressed. These resources were employed to support the development of a modular processing pipeline of TM tools for the robust detection of semantic information in historical medical documents with varying characteristics. We applied the pipeline to two large-scale medical document archives covering wide temporal ranges as the basis for the development of a publicly accessible semantically-oriented search system. The novel resources are available for research purposes, while the processing pipeline and its modules may be used and configured within the Argo TM platform.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0144717