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Generalization of Artificial Intelligence Models in Medical Imaging: A Case-Based Review

arXiv 2211.13230 ↗First posted 15 Nov 2022eess.IV cs.CVcited by 0

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Abstract (arXiv)

The discussions around Artificial Intelligence (AI) and medical imaging are centered around the success of deep learning algorithms. As new algorithms enter the market, it is important for practicing radiologists to understand the pitfalls of various AI algorithms. This entails having a basic understanding of how algorithms are developed, the kind of data they are trained on, and the settings in which they will be deployed. As with all new technologies, use of AI should be preceded by a fundamental understanding of the risks and benefits to those it is intended to help. This case-based review is intended to point out specific factors practicing radiologists who intend to use AI should consider.

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References · 1

  1. 2020Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scanscited by 158

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