Towards an Artificial Intelligence Framework for Data-Driven Prediction of Coronavirus Clinical Severity
Xiangao Jiang1, Megan Coffee2, 3, *, Anasse Bari4, *, Junzhang Wang4, Xinyue Jiang5, Jianping Huang1, Jichan Shi1, Jianyi Dai1, Jing Cai1, Tianxiao Zhang6, Zhengxing Wu1, Guiqing He1, Yitong Huang7
CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 537-551, 2020, DOI:10.32604/cmc.2020.010691
- 30 March 2020
Abstract The virus SARS-CoV2, which causes coronavirus disease (COVID-19) has
become a pandemic and has spread to every inhabited continent. Given the increasing
caseload, there is an urgent need to augment clinical skills in order to identify from among
the many mild cases the few that will progress to critical illness. We present a first step
towards building an artificial intelligence (AI) framework, with predictive analytics (PA)
capabilities applied to real patient data, to provide rapid clinical decision-making
support. COVID-19 has presented a pressing need as a) clinicians are still developing clinical
acumen to this novel… More >