  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.
