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2022 IEEE International Conference on Big Data, Big Data 2022 ; : 6239-6246, 2022.
Article in English | Scopus | ID: covidwho-2284634

ABSTRACT

The pandemic of COVID-19 reminds us of the basic important principles for prevention of infection: avoid the "Three Cs": closed spaces, crowded places and close contact settings. Outpatient clinics in Japan are typical examples of three Cs, where some kinds of decision support system are required to solve the above situation. This paper proposes data mining based patient navigation support system to prevent the Three Cs. Behind the systems, temporal data mining units plays an important role in providing temporal information to the patients, such as waiting time and human densities in the waiting rooms. It analyzes the data stored in hospital information systems, including patient information, logs of clinical orders. The analysis results show that several aspects of patients' waiting are visualized by temporal data mining. © 2022 IEEE.

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