Literature DB >> 34862533

Deployment of Clinical Prediction Models: A Practical Guide to Nomograms and Online Calculators.

Adrian E Jimenez1, James Feghali1, Andrew T Schilling1, Tej D Azad2.   

Abstract

The use of predictive models within neurosurgery is increasing and many models described in published journal articles are made available to readers in formats such as nomograms and online calculators. The present chapter details a step-by-step methodology with accompanying R code that may be used to implement models both in the form of traditional nomograms and as open-access, online calculators through RStudio's Shinyapps. The chapter assumes a basic understanding of predictive modeling in R and utilizes open-access files created by the Machine Intelligence in Clinical Neuroscience (MICN) Lab (Department of Neurosurgery and the Clinical Neuroscience Center of the University Hospital Zurich). When implemented correctly, tools such as nomograms and predictive calculators have the potential to improve user understanding of the underlying statistical models, facilitate broader adoption, and to streamline the eventual use of such models in clinical settings.
© 2022. The Author(s), under exclusive license to Springer Nature Switzerland AG.

Entities:  

Keywords:  Algorithms; Machine learning; Neurosurgery; Nomograms; Outcomes

Mesh:

Year:  2022        PMID: 34862533     DOI: 10.1007/978-3-030-85292-4_13

Source DB:  PubMed          Journal:  Acta Neurochir Suppl        ISSN: 0065-1419


  2 in total

1.  Drawing Nomograms with R: applications to categorical outcome and survival data.

Authors:  Zhongheng Zhang; Michael W Kattan
Journal:  Ann Transl Med       Date:  2017-05

2.  A novel online calculator predicting short-term postoperative outcomes in patients with metastatic brain tumors.

Authors:  Adham M Khalafallah; Adrian E Jimenez; Palak Patel; Sakibul Huq; Omar Azmeh; Debraj Mukherjee
Journal:  J Neurooncol       Date:  2020-09-22       Impact factor: 4.130

  2 in total

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