Introducing novel and comprehensive models for predicting recurrence in breast cancer using the group LASSO approach: are estimates of early and late recurrence different?

BACKGROUND: In here, we constructed personalized models for predicting breast cancer (BC) recurrence according to timing of recurrence (as early and late recurrence). METHODS: An efficient algorithm called group LASSO was used for simultaneous variable selection and risk factor prediction in a logis...

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Detalles Bibliográficos
Autores principales: Akrami, Majid, Arasteh, Peyman, Eghbali, Tannaz, Shahraki, Hadi Raeisi, Tahmasebi, Sedigheh, Zangouri, Vahid, Rezaianzadeh, Abbas, Talei, Abdolrasoul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6136222/
https://www.ncbi.nlm.nih.gov/pubmed/30208904
http://dx.doi.org/10.1186/s12957-018-1489-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6136222/
https://www.ncbi.nlm.nih.gov/pubmed/30208904
http://dx.doi.org/10.1186/s12957-018-1489-0

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