A study of the effectiveness of machine learning methods for classification of clinical interview fragments into a large number of categories Article

Hasan, Mehedi, Kotov, Alexander, Carcone, April Idalski et al. (2016). A study of the effectiveness of machine learning methods for classification of clinical interview fragments into a large number of categories . JOURNAL OF BIOMEDICAL INFORMATICS, 62 21-31. 10.1016/j.jbi.2016.05.004

Open Access

cited authors

  • Hasan, Mehedi; Kotov, Alexander; Carcone, April Idalski; Dong, Ming; Naar, Sylvie; Hartlieb, Kathryn Brogan

sustainable development goals

authors

publication date

  • August 1, 2016

webpage

published in

keywords

  • ADOLESCENTS
  • Annotation of clinical text
  • BEHAVIORS
  • Computer Science
  • Computer Science, Interdisciplinary Applications
  • DIALOGUE
  • Deep learning
  • Life Sciences & Biomedicine
  • Machine learning
  • Medical Informatics
  • Motivational interviewing
  • Science & Technology
  • Technology
  • Text classification

Digital Object Identifier (DOI)

publisher

  • ACADEMIC PRESS INC ELSEVIER SCIENCE

start page

  • 21

end page

  • 31

volume

  • 62