Repository logo
  • English
  • Srpski (lat)
  • Српски
Log In
Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Stanisavljević, D. (23566969700)"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Publication
    Prognostic factors: Classification approaches in patients with lung cancer
    (1997)
    Stanisavljević, D. (23566969700)
    ;
    Jovanović, D. (16236654600)
    ;
    Marinković, J. (7004611210)
    ;
    Milosavljević, M. (7006876926)
    With the proliferation of potential prognostic factors for lung cancer, it is becoming increasingly more difficult to integrate the information provided by these factors into a single accurate prediction of clinical outcome. Here we reviewed five classification methods for their capabilities in classification of 200 patients with lung cancer into distinct prognostic groups using survival outcome as a criteria. The source of patient data for this study is a Lung Tumour Registry from Institute for Lung Diseases, University Clinical Hospital, Belgrade. Almost all developed classification algorithms determined prognostic groups according to biochemical tumour markers LDH and alkaline phosphatase, producing most significant split, instead of commonly used staging variables. The choice of which approach to use for a given classification problem depends not only on statistical properties of method, but also on medical considerations, such as whether more differential findings are given greater weight and the applicability of a classification rule. © 1997, The authors.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Publication
    Prognostic factors: Classification approaches in patients with lung cancer
    (1997)
    Stanisavljević, D. (23566969700)
    ;
    Jovanović, D. (16236654600)
    ;
    Marinković, J. (7004611210)
    ;
    Milosavljević, M. (7006876926)
    With the proliferation of potential prognostic factors for lung cancer, it is becoming increasingly more difficult to integrate the information provided by these factors into a single accurate prediction of clinical outcome. Here we reviewed five classification methods for their capabilities in classification of 200 patients with lung cancer into distinct prognostic groups using survival outcome as a criteria. The source of patient data for this study is a Lung Tumour Registry from Institute for Lung Diseases, University Clinical Hospital, Belgrade. Almost all developed classification algorithms determined prognostic groups according to biochemical tumour markers LDH and alkaline phosphatase, producing most significant split, instead of commonly used staging variables. The choice of which approach to use for a given classification problem depends not only on statistical properties of method, but also on medical considerations, such as whether more differential findings are given greater weight and the applicability of a classification rule. © 1997, The authors.

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Privacy policy
  • End User Agreement
  • Send Feedback