COVID-19 diagnosis based on swin transformer model with demographic information fusion and enhanced multi-head attention mechanism

Author:

Sun Yunlong,Lian Jingge,Teng Ze,Wei Ziyi,Tang Yi,Yang LiuORCID,Gao Yajuan,Wang Tianfu,Li HongfengORCID,Xu Meng,Lei BaiyingORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference42 articles.

1. Pathological findings of COVID-19 associated with acute respiratory distress syndrome;Xu;The Lancet Respiratory Medicine,2020

2. Characteristics and Outcomes of 21 Critically Ill Patients With COVID-19 in Washington State;Arentz;Journal of the American Medical Association,2020

3. Niehus R, De Salazar PM, Taylor AR, Lipsitch M. Quantifying bias of COVID-19 prevalence and severity estimates in Wuhan, China that depend on reported cases in international travelers. medRxiv. 2020:2020.02.13.20022707. doi: 10.1101/2020.02.13.20022707.

4. Early outpatient treatment of symptomatic, high-risk COVID-19 patients that should be ramped-up immediately as key to the pandemic crisis;Risch;American Journal of Epidemiology.,2020

5. To isolate, or not to isolate: A theoretical framework for disease control via contact tracing;Lunz;medRxiv.,2020

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