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Realizing 5G- and AI-based doctor-to-doctor remote diagnosis: opportunities, challenges, and prospects
Kenji Karako1, Peipei Song2, Yu Chen1
1Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
Abstract:
Fifth Generation (5G) mobile communications technology became available in Japan as of the end of March 2020. The Ministry of Internal Affairs and Communications (MIC) is proceeding with a plan to use 5G for a doctor-to-doctor remote diagnosis system. This remote diagnosis offers patients the benefit of receiving advanced medical care without having to travel long distances. The provision of a remote diagnosis will provide elderly patients in rural areas with an earlier diagnosis without burdening patients in Japan where the aging population and the uneven distribution of doctors are increasing. However, the system will increase the burden on specialists by expanding the doctor's catchment area. As a solution to that problem, deep learning-based artificial intelligence (AI) is expected to reduce the burden on doctors. In order to realize 5G- and AI-based real-time diagnostic support, diagnostic imaging using AI and an AI model that provides instructions are required. This is because ultrasonography and endoscopy, which can be used for remote diagnosis, do not acquire data on fixed areas like a CT or MRI scan. The AI model needs to instruct the doctor at the patient's home in order to collect appropriate information in accordance with the patient's symptoms and status. In order to build an interactive AI model, the interactions between doctors who are making a remote diagnosis should be recorded as training data and a 5G-based remote diagnosis system should be created. A remote diagnostic support system incorporating 5G and interactive diagnostic imaging incorporating AI will result in a system that places less of a burden on patients and doctors.
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