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Conference Papers Year : 2018

Guiding Supervised Learning by Bio-Ontologies in Medical Data Analysis

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Janusz Wojtusiak
  • Function : Author
  • PersonId : 1040281
Hua Min
  • Function : Author
  • PersonId : 1040282
Eman Elashkar
  • Function : Author
  • PersonId : 1040283
Hedyeh Mobahi
  • Function : Author
  • PersonId : 1040284

Abstract

Ontologies are popular way of representing knowledge and semantics of data in medical and health fields. Surprisingly, few machine learning methods allow for encoding semantics of data and even fewer allow for using ontologies to guide learning process. This paper discusses the use of data semantics and ontologies in health and medical applications of supervised learning, and particularly describes how the Unified Medical Language System (UMLS) is used within AQ21 rule learning software. Presented concepts are illustrated using two applications based on distinctly different types of data and methodological issues.
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Dates and versions

hal-01950012 , version 1 (10-12-2018)

Licence

Attribution - CC BY 4.0

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Janusz Wojtusiak, Hua Min, Eman Elashkar, Hedyeh Mobahi. Guiding Supervised Learning by Bio-Ontologies in Medical Data Analysis. 4th IFIP International Workshop on Artificial Intelligence for Knowledge Management (AI4KM), Jul 2016, New York, NY, United States. pp.1-18, ⟨10.1007/978-3-319-92928-6_1⟩. ⟨hal-01950012⟩
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