Dynamic-Fusion-Based Federated Learning for COVID-19 Detection.

Medical diagnostic image analysis (e.g., CT scan or X-Ray) using machine learning is an efficient and accurate way to detect COVID-19 infections. However, the sharing of diagnostic images across medical institutions is usually prohibited due to patients' privacy concerns. This causes the issue of insufficient data sets for training the image classification model. Federated learning is an emerging privacy-preserving machine learning paradigm that produces an unbiased global model based on the received local model updates trained by clients without exchanging clients' local data. Nevertheless, the default setting of federated learning introduces a huge communication cost of transferring model updates and can hardly ensure model performance when severe data heterogeneity of clients exists. To improve communication efficiency and model performance, in this article, we propose a novel dynamic fusion-based federated learning approach for medical diagnostic image analysis to detect COVID-19 infections. First, we design an architecture for dynamic fusion-based federated learning systems to analyze medical diagnostic images. Furthermore, we present a dynamic fusion method to dynamically decide the participating clients according to their local model performance and schedule the model fusion based on participating clients' training time. In addition, we summarize a category of medical diagnostic image data sets for COVID-19 detection, which can be used by the machine learning community for image analysis. The evaluation results show that the proposed approach is feasible and performs better than the default setting of federated learning in terms of model performance, communication efficiency, and fault tolerance.

Trustworthy and Intelligent COVID-19 Diagnostic IoMT Through XR and Deep-Learning-Based Clinic Data Access.

This article presents a novel extended reality (XR) and deep-learning-based Internet-of-Medical-Things (IoMT) solution for the COVID-19 telemedicine diagnostic, which systematically combines virtual reality/augmented reality (AR) remote surgical plan/rehearse hardware, customized 5G cloud computing and deep learning algorithms to provide real-time COVID-19 treatment scheme clues. Compared to existing perception therapy techniques, our new technique can significantly improve performance and security. The system collected 25 clinic data from the 347 positive and 2270 negative COVID-19 patients in the Red Zone by 5G transmission. After that, a novel auxiliary classifier generative adversarial network-based intelligent prediction algorithm is conducted to train the new COVID-19 prediction model. Furthermore, The Copycat network is employed for the model stealing and attack for the IoMT to improve the security performance. To simplify the user interface and achieve an excellent user experience, we combined the Red Zone's guiding images with the Green Zone's view through the AR navigate clue by using 5G. The XR surgical plan/rehearse framework is designed, including all COVID-19 surgical requisite details that were developed with a real-time response guaranteed. The accuracy, recall, F1-score, and area under the ROC curve (AUC) area of our new IoMT were 0.92, 0.98, 0.95, and 0.98, respectively, which outperforms the existing perception techniques with significantly higher accuracy performance. The model stealing also has excellent performance, with the AUC area of 0.90 in Copycat slightly lower than the original model. This study suggests a new framework in the COVID-19 diagnostic integration and opens the new research about the integration of XR and deep learning for IoMT implementation.

Research Progress of Genetic Structure, Pathogenic Mechanism, Clinical Characteristics, and Potential Treatments of Coronavirus Disease 2019.

Coronavirus disease 2019 (COVID-19) is a global pandemic infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), and currently affects more than 8 million people worldwide. SARS-CoV-2 mainly invades the cells by binding to the angiotensin converting enzyme 2 (ACE2) receptor, leading to the injury of respiratory system, cardiovascular system, digestive system, and urinary system, and even secondary to acute respiratory distress syndrome (ARDS) and systemic inflammatory response, resulting in multiple organ failure. In this review, mainly focusing on biogenesis and pathogenic mechanisms, we describe the recent progress in our understanding of SARS-CoV-2 and then summarize and discuss its crucial clinical characteristics and potential mechanism in different systems. Additionally, we discuss the potential treatments for COVID-19, aiming at a better understanding of the pathogenesis of SARS-CoV-2 and providing new ideas for the personalized treatment of COVID-19.

[Study on medication regularity of traditional Chinese medicine in treatment of COVID-19 based on data mining].

The coronavirus disease 2019(COVID-19) is developing rapidly and posing great threat to public health. There is no specific medicine available for treating the disease. Luckily, traditional Chinese medicine has played a positive role in the fighting against COVID-19. In this paper, We collected and sorted the prescriptions of modern Chinese medicine for COVID-19 released by national government, different provinces, autonomous regions and municipalities, as well as online databases, such as CNKI, WanFang medical network, and VIP database. These prescriptions were combined with the inheritance of traditional Chinese medicine auxiliary V2.5, and the complex system entropy clustering method was used to determine the association rules and frequency of single drug and drug combination in the prescription. In the end, 96 effective prescriptions were included. Among them, the four properties were mainly concentrated in temperature, cold and level, the five tastes were mainly concentrated in bitter, hot and sweet, and the meridians were mainly concentrated in lung, stomach and spleen. The high-frequency drugs were Glycyrrhizae Radix et Rhizoma, Armeniacae Semen Amarum, Gypsum Fibrosum, etc., and the high-frequency combinations are Gypsum Fibrosum-Armeniacae Semen Amarum, Gypsum Fibrosum-Glycyrrhizae Radix et Rhizoma, Armeniacae Semen Amarum-Glycyrrhizae Radix et Rhizoma, the core combinations are Lepidii Semen-Armeniacae Semen Amarum-Gypsum Fibrosum, Pogostemonis Herba-Zingiberis Rhizoma Recens-Magnoliae Officinalis Cortex, Ophiopogonis Radix-Armeniacae Semen Amarum-Scutellariae Radix and so on. Form new prescriptions Lepidii Semen, Armeniacae Semen Amarum, Gypsum Fibrosum, Pogostemonis Herba, Zingiberis Rhizoma Recens, Magnoliae Officinalis Cortex. Ophiopogonis Radix, Armeniacae Semen Amarum, Scutellariae Radix, Schisandrae Sphenantherae Fructus, Panacis Quinquefolii Radix. From the medicinal properties to high-frequency drugs and new prescriptions, it could be seen that the overall treatment of COVID-19 by traditional Chinese medicine was to strengthen body resistance, eliminate pathogenic factors, and give attention to Qi and Yin.