Developing tools and resources for the biomedical domain of the Greek language

Vagelatos, Aristides; Elena, Mantzari; Pantazara, Mavina; Tsalidis, Christos; Kalamara, C.

doi:10.1177/1460458211405007

Cited by 5 publications

(4 citation statements)

References 17 publications

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“…There is sustained interest in terminology development and the integration of terminologies and ontologies in the UMLS [ 50 ], or SNOMED-CT for languages such as Basque [ 51 ]. In other cases, full resource suites including terminologies, NLP modules, and corpora have been developed, such as for Greek [ 52 ] and German [ 53 ].…”

Section: Main Textmentioning

confidence: 99%

Clinical Natural Language Processing in languages other than English: opportunities and challenges

et al. 2018

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BackgroundNatural language processing applied to clinical text or aimed at a clinical outcome has been thriving in recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) for languages other than English. Recent studies are summarized to offer insights and outline opportunities in this area.Main BodyWe envision three groups of intended readers: (1) NLP researchers leveraging experience gained in other languages, (2) NLP researchers faced with establishing clinical text processing in a language other than English, and (3) clinical informatics researchers and practitioners looking for resources in their languages in order to apply NLP techniques and tools to clinical practice and/or investigation. We review work in clinical NLP in languages other than English. We classify these studies into three groups: (i) studies describing the development of new NLP systems or components de novo, (ii) studies describing the adaptation of NLP architectures developed for English to another language, and (iii) studies focusing on a particular clinical application.ConclusionWe show the advantages and drawbacks of each method, and highlight the appropriate application context. Finally, we identify major challenges and opportunities that will affect the impact of NLP on clinical practice and public health studies in a context that encompasses English as well as other languages.

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Section: Main Textmentioning

confidence: 99%

Clinical Natural Language Processing in languages other than English: opportunities and challenges

et al. 2018

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“…The other two articles in this special issue (Vagelatos et al, 17 Maragoudakis and Maglogiannis 18 ) deal with the issue of developing the knowledge and linguistic resources that are necessary for the indexing, labelling and retrieval of health-related web resources. Whereas the work by Vagelatos et al exploits textual corpora for the creation of a biomedical ontology, Maragoudakis and Maglogiannis process web image data for the creation of a dermatological ontology.…”

mentioning

confidence: 99%

“…Whereas the work by Vagelatos et al exploits textual corpora for the creation of a biomedical ontology, Maragoudakis and Maglogiannis process web image data for the creation of a dermatological ontology. 17,18 Both approaches are necessary in order to index health-related multimedia web content.…”

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confidence: 99%

“…17,19 This led to the creation of the first biomedical ontology for the Greek language, adopting the Unified Medical Language System ® (UMLS) Semantic Network (SN) as an initial top-level ontology, mapping it onto Greek and enriching it with Greek biomedical terms, processing existing dictionaries and glossaries, as well as extracting additional terms from a large corpus of biomedical texts. The final version of the IATROLEXI ontology involves 14,000 concepts represented by 16,500 terms.…”

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confidence: 99%

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Special issue on semantic descriptions of medical web resources

Karkaletsis

Mayer

Karampiperis

2011

Health Informatics J

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The internet is designed for direct use by people searching for information through their browsers; accessing health-related information has never been easier. The increasing amount of freelyavailable, health-related web content creates, on the one hand, excellent conditions for selfeducation of patients as well as physicians but, on the other hand, however, it entails substantial risks if such information is trusted, irrespective of the low competence, or even bad intentions, of its authors. Furthermore, it is difficult for health information consumers, such as patients and the general public, to assess, by themselves, the quality of the information, as they are not always familiar with medical domains and vocabularies.

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