Using Multivariate Regression Model with Least Absolute Shrinkage and Selection Operator (LASSO) to Predict the Incidence of Xerostomia after Intensity-Modulated Radiotherapy for Head and Neck Cancer

标题
Using Multivariate Regression Model with Least Absolute Shrinkage and Selection Operator (LASSO) to Predict the Incidence of Xerostomia after Intensity-Modulated Radiotherapy for Head and Neck Cancer
作者
关键词
Parotid glands, Prognosis, Cancer treatment, Radiation therapy, Finance, Dose prediction methods, Forecasting, Chemotherapy
出版物
PLoS One
Volume 9, Issue 2, Pages e89700
出版商
Public Library of Science (PLoS)
发表日期
2014-03-01
DOI
10.1371/journal.pone.0089700

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Publish scientific posters with Peeref

Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.

Learn More

Find the ideal target journal for your manuscript

Explore over 38,000 international journals covering a vast array of academic fields.

Search