Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database-Reference-Cited by-同舟云学术

Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database

Published:2021-03 Issue:3 Volume:3 Page:e158-e165
ISSN:2589-7500
Container-title:The Lancet Digital Health
language:en
Short-container-title:The Lancet Digital Health

Author:

Lee Changhee,Light Alexander,Alaa Ahmed,Thurtle David,van der Schaar Mihaela,Gnanapragasam Vincent J

Publisher

Elsevier BV

Subject

Health Information Management,Decision Sciences (miscellaneous),Health Informatics,Medicine (miscellaneous)

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4. Follow-up of prostatectomy versus observation for early prostate cancer;Wilt;N Engl J Med,2017

5. Improving clinical risk stratification at diagnosis in primary prostate cancer: a prognostic modelling study;Gnanapragasam;PLoS Med,2016

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