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Extended endocrine therapy in breast cancer: A basket of length-constraint feature selection metaheuristics to balance Type I against Type II errors.
Liu, Hua-Ping; Zhang, Jian V; Wang, Dongwen; Albrecht, Andreas; Steinhöfel, Kathleen; Lai, Hung-Ming.
Afiliación
  • Liu HP; Center for Energy Metabolism and Reproduction, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen Key Laboratory of Metabolic Health, Shenzhen 518055, China; National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital &amp
  • Zhang JV; Center for Energy Metabolism and Reproduction, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen Key Laboratory of Metabolic Health, Shenzhen 518055, China; Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055,
  • Wang D; National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China.
  • Albrecht A; School of Science and Technology, Middlesex University, London NW4 4BT, United Kingdom.
  • Steinhöfel K; Department of Informatics, King's College London, London WC2B 4BG, United Kingdom. Electronic address: kathleen.steinhofel@kcl.ac.uk.
  • Lai HM; Department of Informatics, King's College London, London WC2B 4BG, United Kingdom; Aiphaqua Genomics Research Unit, Taipei 111, Taiwan. Electronic address: hmlai@aiphaqua.com.
J Biomed Inform ; 131: 104112, 2022 07.
Article en En | MEDLINE | ID: mdl-35680073
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Prognostic_studies Aspecto: Patient_preference Límite: Female / Humans Idioma: En Revista: J Biomed Inform Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Prognostic_studies Aspecto: Patient_preference Límite: Female / Humans Idioma: En Revista: J Biomed Inform Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos