30 Apr 2021
Although a plethora of research articles on AI methods on COVID-19 medical imaging are published, their clinical value remains unclear. We conducted the largest systematic review of the literature addressing the utility of AI in imaging for COVID-19 patient care. By keyword searches on PubMed and preprint servers throughout 2020, we identified 463 manuscripts and performed a systematic meta-analysis to assess their technical merit and clinical relevance. Our analysis evidences a significant disparity between clinical and AI communities, both in the focus on imaging modalities (AI experts neglected CT and Ultrasound, favoring X-Ray) and performed tasks (71.9% of AI papers centered on diagnosis). The vast majority of manuscripts were found deficient regarding potential use in clinical practice, but 2.7% (N=12) publications were assigned a high maturity level and are summarized in greater detail. We provide an itemized discussion of the challenges in developing clinically relevant AI solutions with recommendations and remedies.