Common Pitfalls in Machine Learning for Radiology

I stumbled on this paper from a link; it has irrefutable arguments. I think it is worth your time.

Roberts, Michael, Derek Driggs, Matthew Thorpe, Julian Gilbey, Michael Yeung, Stephan Ursprung, Angelica I. Aviles-Rivero, et al. 2021. “Common Pitfalls and Recommendations for Using Machine Learning to Detect and Prognosticate for COVID-19 Using Chest Radiographs and CT Scans.” Nature Machine Intelligence 3 (3): 199–217. https://doi.org/10.1038/s42256-021-00307-0.

[embeddoc url=”https://www.nature.com/articles/s42256-021-00307-0.pdf”%5D

The summary is here:

[embeddoc url=”https://radoncnotescom.files.wordpress.com/2022/01/40d25-roberts_etal_commonpitfallsrecommendationsusingmachine_2021.docx”%5D

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