• COVID-19
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The world has been facing the COVID-19 pandemic since December 2019. Timely and efficient diagnosis of COVID-19 suspected patients plays a significant role in medical treatment. The deep transfer learning-based automated COVID-19 diagnosis on chest X-ray is required to counter the COVID-19 outbreak. This work proposes a real-time Internet of Things (IoT) framework for early diagnosis of suspected COVID-19 patients by using ensemble deep transfer learning. The proposed framework offers real-time communication and diagnosis of COVID-19 suspected cases. The proposed IoT framework ensembles four deep learning models such as InceptionResNetV2, ResNet152V2, VGG16, and DenseNet201. The medical sensors are utilized to obtain the chest X-ray modalities and diagnose the infection by using the deep ensemble model stored on the cloud server. The proposed deep ensemble model is compared with six well-known transfer learning models over the chest X-ray dataset. Comparative analysis revealed that the proposed model can help radiologists to efficiently and timely diagnose the COVID-19 suspected patients.

Abstract As physical distancing is a core measure of containing the spread of COVID-19, this pandemic is a crisis that has uprooted social interaction. While current research mainly focuses on crises as a challenge for entrepreneurial ventures and potential regulatory response mechanisms, we complement this research by addressing the question of how crises in general—and COVID-19’s physical distancing measures in particular—shape entrepreneurial opportunities for social innovation. Based on two rounds of data collection—desktop research mapping out 95 entrepreneurial activities in Germany and four focus groups—we find first that entrepreneurs are proactive agents in alleviating the negative consequences of the COVID-19 crisis. They do so by creating two types of digital social innovation: digital brokering and digitized services. Second, we note that negative societal consequences of crises can be buffered by shifts in entrepreneurs’ strategic orientation through improvised venturing, rapid pivoting and pro-social product extension. Third, we note variance in the persistence of changes with consequences for entrepreneurial opportunities and social innovation: Whereas some social innovation are rather ephemeral, others might endure and promise long-term impacts. We offer key insights for the literature on crisis, social innovation and hybrid organizing as well as on the implications for entrepreneurship practice and policy.