Sample-Size Determination Methodologies for Machine Learning in Medical Imaging Research: A Systematic Review

2019290 citationsReview

Authors

Indranil Balki · University of Toronto

Afsaneh Amirabadi · University of Toronto

Jacob Levman · Boston Children's Hospital

Anne L. Martel · University of Toronto

Žiga Emeršič · University of Ljubljana

Blaž Meden · University of Ljubljana

Ángel García‐Pedrero ·

Abstract

Our study highlights the scarcity of research in training set size determination methodologies applied to ML in medical imaging, emphasizes the need to standardize current reporting practices, and guides future work in development and streamlining of pre hoc and post hoc sample size approaches.

Topics & Keywords

Artificial Intelligence in Healthcare and Education Radiomics and Machine Learning in Medical Imaging AI in cancer detection

Publication Details

Published in: Canadian Association of Radiologists Journal

Volume 70, Issue 4, pp. 344-353

DOI: 10.1016/j.carj.2019.06.002

Field-Weighted Citation Impact: 6.82

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Sample-Size Determination Methodologies for Machine Learning in Medical Imaging Research: A Systematic Review

Authors

Abstract

Topics & Keywords

Publication Details