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- W3190193670 abstract "Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. Intelligent science(IS) is an interdisciplinary subject which dedicates to joint research on informatics and technology of intelligence by brain science, artificial intelligence(AI), cognitive science, data science and others. IS is devoted to create intelligent computer software that models the human behavior. The main goal of IS is to make computers smarter by creating intelligent algorithms that will allow a computer to mimic some of the functions of the human brain in selected applications. All of these applications employ knowledge base and inferencing techniques to solve problems or help make decisions in specific domains. This talk discusses the potential role of intelligence science, AI methodologies, knowledge engineering and intelligent computing paradigms, for smart detection and diagnosis of Corona virus, COVID-19. The talk presents the following issues; (a) detection intelligent software for people who have Corona virus, (b) super computing power resources to assist professors with research on the corona virus, (c) intelligent medical imaging evaluation systems, (d) facial recognition intelligent algorithms and thermal imaging temperature measurement technology, and (e) deep learning technique for detection of COVID-19 using X-Ray images. Moreover, the talk presents a proposal for case-based reasoning expert system for corona, COVID-19 diagnosis. In addition, the talk presents the research directions and some examples of the developed intelligent healthcare systems by the author and his colleagues at AIKER-Labs." @default.
- W3190193670 created "2021-08-16" @default.
- W3190193670 creator A5061699800 @default.
- W3190193670 date "2020-12-12" @default.
- W3190193670 modified "2023-09-27" @default.
- W3190193670 title "Keynote Speech III: Intelligence Science for Smart Detection and Diagnosis of Corona Virus" @default.
- W3190193670 doi "https://doi.org/10.1109/iccta52020.2020.9477654" @default.
- W3190193670 hasPublicationYear "2020" @default.
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