Weijie Zhu

BACKGROUND: The outbreak of COVID-19 has caused a continuing global pandemic. Hospitals are integral to the control and prevention of COVID-19; however, they are facing numerous challenges during the epidemic. OBJECTIVE: Our study aimed to introduce the practical experience of the design and implementation of a web-based COVID-19 service platform at a tertiary hospital in China as well as the preliminary results of the implementation. METHODS: The web-based COVID-19 service platform was deployed within the health care system of the Guangdong Second Provincial General Hospital and Internet Hospital; the function of the platform was to provide web-based medical services for both members of the public and lay health care workers. The focal functions of this system included automated COVID-19 screening, related symptom monitoring, web-based consultation, and psychological support; it also served as a COVID-19 knowledge hub. The design and process of each function are introduced. The usage data for the platform service were collected and are represented by three periods: the pre-epidemic period (December 22, 2019, to January 22, 2020, 32 days), the controlled period (January 23 to March 31, 2020, 69 days), and the postepidemic period (April 1 to June 30, 2020, 91 days). RESULTS: By the end of June 2020, 96,642 people had used the automated COVID-19 screening and symptom monitoring systems 161,884 and 7,795,194 times, respectively. The number of general web-based consultation services per day increased from 30 visits in the pre-epidemic period to 122 visits during the controlled period, then dropped to 73 visits in the postepidemic period. The psychological counseling program served 636 clients during the epidemic period. For people who used the automated COVID-19 screening service, 160,916 (99.40%) of the total users were classified in the no risk category. 464 (0.29%) of the people were categorized as medium to high risk, and 12 people (0.01%) were recommended for further COVID-19 testing and treatment. Among the 96,642 individuals who used the COVID-19 related symptoms monitoring service, 6696 (6.93%) were symptomatic at some point during the monitoring period. Fever was the most frequently reported symptom, with 2684/6696 symptomatic people (40.1%) having had this symptom. Cough and sore throat were also relatively frequently reported by the 6696 symptomatic users (1657 people, 24.7%, and 1622 people, 24.2%, respectively). CONCLUSIONS: The web-based COVID-19 service platform implemented at a tertiary hospital in China is exhibited to be a role model for using digital health technologies to respond to the COVID-19 pandemic. The digital solutions of automated COVID-19 screening, daily symptom monitoring, web-based care, and knowledge propagation have plausible acceptability and feasibility for complementing offline hospital services and facilitating disease control and prevention.

Passive mode-locked fiber lasers (PMLFLs) have great advantages in generating ultrashort pulses due to their unique parameter tunability. The pulse duration, energy and peak power can be controlled by parameter tuning. Here, Kolmogorov-Arnold network (KAN) algorithm is used to predict the pulse characteristics of PMLFLs, and several optimization algorithms are used to explore the optimal output and parameters' combination. Firstly, we obtain the dataset between different parameters and pulse characteristics by solving the PMLFL model. Then, KAN algorithm is used to interpret and predict the data set, and the function between input parameters and ultrashort pulse is obtained. We compare KAN to a series of traditional machine learning (ML) models, and KAN is more efficiently than traditional ML models. Then we use ensemble learning to design a multi-mechanism prediction model to enhance the robustness of the prediction model. Finally, we use particle swarm optimization (PSO) to optimize the KAN model, and compare the optimization results with other intelligent algorithms for the traditional ML model. The KAN prediction model and explicit function are helpful to optimize the parameter setting of optical communication system, laser processing system and laser medical system, and improve the communication quality, processing quality and treatment effect.

The COVID-19 pandemic has resulted in nosocomial transmission of COVID-19 within hospitals and other healthcare settings such as residential homes and primary care settings. Here, we discuss how a 5G network can be used to reduce such infections. Wen et al. discuss how implementing a 5G network in hospitals can be used to reduce nosocomial infections. Such systems can reduce the spread of COVID-19.