| Literature DB >> 32890777 |
Hayit Greenspan1, Raúl San José Estépar2, Wiro J Niessen3, Eliot Siegel4, Mads Nielsen5.
Abstract
In this position paper, we provide a collection of views on the role of AI in the COVID-19 pandemic, from clinical requirements to the design of AI-based systems, to the translation of the developed tools to the clinic. We highlight key factors in designing system solutions - per specific task; as well as design issues in managing the disease at the national level. We focus on three specific use-cases for which AI systems can be built: early disease detection, management in a hospital setting, and building patient-specific predictive models that require the combination of imaging with additional clinical data. Infrastructure considerations and population modeling in two European countries will be described. This pandemic has made the practical and scientific challenges of making AI solutions very explicit. A discussion concludes this paper, with a list of challenges facing the community in the AI road ahead.Entities:
Keywords: AI; COVID-19; Imaging
Mesh:
Year: 2020 PMID: 32890777 PMCID: PMC7437567 DOI: 10.1016/j.media.2020.101800
Source DB: PubMed Journal: Med Image Anal ISSN: 1361-8415 Impact factor: 8.545