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

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

Abstract 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...

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Bibliographic Details
Main Authors: Majid Akrami, Peyman Arasteh, Tannaz Eghbali, Hadi Raeisi Shahraki, Sedigheh Tahmasebi, Vahid Zangouri, Abbas Rezaianzadeh, Abdolrasoul Talei
Format: Article
Language:English
Published: BMC 2018-09-01
Series:World Journal of Surgical Oncology
Subjects:
Breast cancer
Early
Late
Recurrence
Prediction
Model
Online Access:http://link.springer.com/article/10.1186/s12957-018-1489-0

Internet

http://link.springer.com/article/10.1186/s12957-018-1489-0

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