Predicting 180-day mortality for women with ovarian cancer using machine learning and patient-reported outcome data

HIGHLIGHTS

• who: Chris J. Sidey-Gibbons from the University of have published the research work: Predicting 180-day mortality for women with ovarian cancer using machine learning and patient-reported outcome data, in the Journal: Scientific Reports Scientific Reports of 13/01/2022
• what: In this manuscript, the authors attempt to create a solution to the issue of poor prognostication around the end-of-life by using longitudinal PRO data to develop a novel ML algorithm to accurately and sensitively predict transition to end-of-life for women with ovarian cancer. This approach has been shown . . .
  

   

  

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

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

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