The importance of being external. methodological insights for the external validation of machine learning models in medicine-Reference-Cited by-同舟云学术

The importance of being external. methodological insights for the external validation of machine learning models in medicine

Published:2021-09 Issue: Volume:208 Page:106288
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Cabitza Federico^ORCID,Campagner Andrea^ORCID,Soares Felipe^ORCID,García de Guadiana-Romualdo Luis,Challa Feyissa^ORCID,Sulejmani Adela,Seghezzi Michela,Carobene Anna

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference70 articles.

1. Estimating kullback-leibler divergence using kernel machines;Ahuja,2019

2. Minimum sample size for external validation of a clinical prediction model with a continuous outcome;Archer;Stat Med,2021

3. Application of deep learning technique to manage covid-19 in routine clinical practice using ct images: results of 10 convolutional neural networks;Ardakani;Comput. Biol. Med.,2020

4. Challenges to the reproducibility of machine learning models in health care;Beam;JAMA,2020

5. External validation is necessary in prediction research:: a clinical example;Bleeker;J Clin Epidemiol,2003

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