Efficacy of interferon treatment for chronic hepatitis C predicted by Feature Subset Selection and Support Vector Machine.

Detalles Bibliográficos
Publicado en:Journal of Medical Systems Vol. 31; no. 2; pp. 117 - 124
Autores principales: Yang J, Nugroho AS, Yamauchi K, Yoshioka K, Zheng J, Wang K, Kato K, Kuroyanagi S, Iwata A
Formato: equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Apr2007
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Efficacy of interferon treatment for chronic hepatitis C predicted by Feature Subset Selection and Support Vector Machine.
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          Yang J
          Nugroho AS
          Yamauchi K
          Yoshioka K
          Zheng J
          Wang K
          Kato K
          Kuroyanagi S
          Iwata A
        affil: Department of Medical Information and Management Science, Graduate School of Medicine, Nagoya University, 65, Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan. junyang@med.nagoya-u.ac.jp
      sug:
        subj:
          Decision Support Systems, Clinical Administration
          Hepatitis C, Chronic Drug Therapy
          Interferons Therapeutic Use
          Adolescence
          Adult
          Aged
          Biopsy
          Female
          Funding Source
          Genotype
          Hepatitis C, Chronic Blood
          Liver Function Tests
          Male
          Middle Age
          RNA Blood
          Human
          Adolescent: 13-18 years
          Adult: 19-44 years
          Aged: 65+ years
          Middle Aged: 45-64 years
          Female
          Male
      pubtype: Academic Journal
      doctype:
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        research
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    language: English
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