In recent years, I have been carrying out research in the area of information techniques for medical treatment. Specifically, my research focuses on solving the key problems that restrict the wide application of the Internet of things (IoT) for medical treatment, and I have lead my team to develop new technologies on smart medical terminals and digital healthcare platforms. Currently, my research team has successfully constructed a complete technology architecture for medical healthcare based on IoT, which is characterized by accurate perception, reliable transmission, highly sharing and deep mining. Under this technology architecture, we have developed of three novel medical IoT systems, i.e., the Rainbow Cloud System (RCS) for rural medical care, the Home Cloud System (HCS) for home and aging care, the Following-up Cloud System (FCS) for hospital revisit and trace to patients. Based on the developed medical information systems, I have also explored the innovated modes and mechanisms for the future intelligently medical treatment. These work laid the foundation for the proposed research to develop data mining and machine learning methods for the big noncoded amino acids (ncAAs) data.
We have overcome the challenges in the sensing of the extremely weak biological signals. The advanced interference suppressing techniques have been developed and the signals can be extracted and amplified efficiently. We have also developed key techniques for the scalability and standardization of the intelligent medical data processing, which help to construct medical IoT terminals with miniaturized size, low cost, easy operation, and dynamic expansion, etc. By applying deep learning techniques in our terminals, we have made the terminals much smarter
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