Machine learning can identify newly diagnosed patients with cll at high risk of infection

HIGHLIGHTS

• who: Rudi Agius from the Technical University Chicago, Chicago, IL, USA have published the paper: Machine learning can identify newly diagnosed patients with CLL at high risk of infection, in the Journal: NATURE COMMUNICATIONS NATURE COMMUNICATIONS
• what: Previously, models in CLL have focused on the prediction of progression - or treatment-free survival, and OS9-11 - predictive models that combine treatment and infection as an outcome, such as the authors propose, have not yet been explored. Through the online version of CLL-TIM, CLL-TIM.org, the authors provide explainable predictions by accompanying them with uncertainty . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.