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

• URL: http://arxiv.org/abs/2110.12464v1
• Date: Sun, 24 Oct 2021 15:28:18 GMT
• Title: Requirement analysis for an artificial intelligence model for the diagnosis of the COVID-19 from chest X-ray data
• Authors: Tuomo Kalliokoski
• Abstract summary: 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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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