Trustworthy and Intelligent COVID-19 Diagnostic IoMT through XR and Deep Learning-based Clinic Data Access

This paper presents a novel XR and Deep Learning-based IoMT solution for the COVID-19 telemedicine diagnostic, which systematically combines VR/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 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 ACGAN-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 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 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 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 IEEE