Each year, over 2.5 million people, most of them in developed countries, die from pneumonia [1]. Since many studies have proved pneumonia is successfully treatable when timely and correctly diagnosed, many of diagnosis aids have been developed, with AI-based methods achieving high accuracies [2]. However, currently, the usage of AI in pneumonia detection is limited, in particular, due to challenges in generalizing a locally achieved result. In this report, we propose a roadmap for creating and integrating a system that attempts to solve this challenge. We also address various technical, legal, ethical, and logistical issues, with a blueprint of possible solutions.
@article{arxiv.2012.03487,
title = {An Approach to Intelligent Pneumonia Detection and Integration},
author = {Bonaventure F. P. Dossou and Alena Iureva and Sayali R. Rajhans and Vamsi S. Pidikiti},
journal= {arXiv preprint arXiv:2012.03487},
year = {2020}
}