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

The required training sample size for a particular machine learning (ML) model applied to medical imaging data is often unknown. The purpose of this study was to provide a descriptive review of current sample-size determination methodologies in ML applied to medical imaging and to propose recommendations for future work in the field.

Source: Canadian Association of Radiologists Journal - September 11, 2019 Category: Radiology Authors: Indranil Balki, Afsaneh Amirabadi, Jacob Levman, Anne L. Martel, Ziga Emersic, Blaz Meden, Angel Garcia-Pedrero, Saul C. Ramirez, Dehan Kong, Alan R. Moody, Pascal N. Tyrrell Tags: Critically Appraised Topic / Évaluation critique Source Type: research