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Requirement analysis for an artificial intelligence model for the diagnosis of the COVID-19 from chest X-ray data

arXiv 2110.12464 ↗First posted 24 Oct 2021eess.IV cs.CV cs.LGcited by 0

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Abstract (arXiv)

There are multiple papers published about different AI models for the COVID-19 diagnosis with promising results. Unfortunately according to the reviews many of the papers do not reach the level of sophistication needed for a clinically usable model. In this paper I go through multiple review papers, guidelines, and other relevant material in order to generate more comprehensive requirements for the future papers proposing a AI based diagnosis of the COVID-19 from chest X-ray data (CXR). Main findings are that a clinically usable AI needs to have an extremely good documentation, comprehensive statistical analysis of the possible biases and performance, and an explainability module.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 100 references that are in the map. First posted on arXiv 24 Oct 2021.

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19 of 100 references.

References · 19

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7 more
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