Web: http://arxiv.org/abs/2112.12705

June 23, 2022, 1:11 a.m. | Felipe Giuste, Wenqi Shi, Yuanda Zhu, Tarun Naren, Monica Isgut, Ying Sha, Li Tong, Mitali Gupte, May D. Wang

cs.LG updates on arXiv.org arxiv.org

Despite the myriad peer-reviewed papers demonstrating novel Artificial
Intelligence (AI)-based solutions to COVID-19 challenges during the pandemic,
few have made significant clinical impact. The impact of artificial
intelligence during the COVID-19 pandemic was greatly limited by lack of model
transparency. This systematic review examines the use of Explainable Artificial
Intelligence (XAI) during the pandemic and how its use could overcome barriers
to real-world success. We find that successful use of XAI can improve model
performance, instill trust in the end-user, …

ai artificial artificial intelligence arxiv explainable artificial intelligence intelligence pandemics review

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