Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model.

Rupapara, Vaibhav; Rustam, Furqan; Aljedaani, Wajdi; Shahzad, Hina Fatima; Lee, Ernesto; Ashraf, Imran

Rupapara, Vaibhav; Rustam, Furqan; Aljedaani, Wajdi; Shahzad, Hina Fatima; Lee, Ernesto; Ashraf, Imran.

Afiliación

Rupapara V; School of Computing and Information Sciences, Florida International University, University Park, USA.
Rustam F; Department of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, 64200, Pakistan.
Aljedaani W; Department of Computer Science and Engineering, University of North Texas, Denton, TX, USA.
Shahzad HF; Department of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, 64200, Pakistan.
Lee E; Department of Computer Science, Broward College, Broward County, FL, USA. elee@broward.edu.
Ashraf I; Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38544, South Korea. imranashraf@ynu.ac.kr.

Sci Rep ; 12(1): 1000, 2022 01 19.

Article en En | MEDLINE | ID: mdl-35046459

Asunto(s)

Neoplasias Hematológicas/diagnóstico; Neoplasias Hematológicas/genética; Leucemia/genética; Aprendizaje Automático Supervisado; Neoplasias Hematológicas/clasificación; Humanos; Modelos Logísticos; Análisis por Micromatrices

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Leucemia / Neoplasias Hematológicas / Aprendizaje Automático Supervisado Tipo de estudio: Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

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