The intelligent prognosis is in an urgent need to assist physicians to take an early intervention, prevent the adverse outcome, and optimize the medical resource allocation . In the early stage of the epidemic outbreak, the data available for analysis is limited due to the lack of effective diagnostic mechanisms, rarity of the cases, and privacy concerns . In this paper, we propose a deep-learning-based approach, CovidCare, which leverages the existing electronic medical records to enhance the prognosis for inpatients with emerging infectious diseases . It learns to embed the COVID-19-related medical features based on massive existing EMR data via transfer learning . The researchers also trained to imitate the teacher model’s representation behavior based on knowledge distillation . Normal values of gamma-GT, AP and eGFR indicate the overall improvement of health. The medical findings extracted by CovideCare are empirically confirmed by human experts and medical literatures. The findings extracted . are empiricalically confirmed and are empirically confirmed by humans and medical experimentally studying the medical findings from the model are confirmed by human experts and medical literatures and medical literatures . The model consistently outperforms

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Keywords : medical - nbsp - confirmed - prognosis - based -

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