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The Use of Natural Language Processing for Market Orientation on Rare Diseases
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Author(s): Matthias Hölscher (Institute for IT Management and Digitization, FOM University, Germany)and Rudiger Buchkremer (Institute for IT Management and Digitization, FOM University, Germany)
Copyright: 2021
Pages: 21
Source title:
Natural Language Processing for Global and Local Business
Source Author(s)/Editor(s): Fatih Pinarbasi (Istanbul Medipol University, Turkey)and M. Nurdan Taskiran (Istanbul Medipol University, Turkey)
DOI: 10.4018/978-1-7998-4240-8.ch010
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Abstract
Rare diseases in their entirety have a substantial impact on the healthcare market, as they affect a large number of patients worldwide. Governments provide financial support for diagnosis and treatment. Market orientation is crucial for any market participant to achieve business profitability. However, the market for rare diseases is opaque. The authors compare results from search engines and healthcare databases utilizing natural language processing. The approach starts with an information retrieval process, applying the MeSH thesaurus. The results are prioritized and visualized, using word clouds. In total, the chapter is about the examination of 30 rare diseases and about 500,000 search results in the databases Pubmed, FindZebra, and the search engine Google. The authors compare their results to the search for common diseases. The authors conclude that FindZebra and Google provide relatively good results for the evaluation of therapies and diagnoses. However, the quantity of the findings from professional databases such as Pubmed remains unsurpassed.
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