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http://dx.doi.org/10.9717/kmms.2022.25.2.345

Research on the development of demand for medical and bio technology using big data  

Lee, Bongmun. (CKU center for health policy research., Catholic Kwandong University)
Nam, Gayoung (CKU center for health policy research., Catholic Kwandong University)
Kang, Byeong Chul (D.iF,Inc., Byeong-Chul Kang)
Kim, CheeYong (Major of Game Engineering, Dong-Eui University)
Publication Information
Journal of Korea Multimedia Society / v.25, no.2, 2022 , pp. 345-352 More about this Journal
Abstract
Conducting AI-based fusion business due to the increment of ICT fusion medical device has been expanded. In addition, AI-based medical devices help change existing medical system on treatment into the paradigm of customized treatment such as preliminary diagnosis and prevention. It will be generally promoted to the change of medical device industry. Although the current demand forecasting of medical biotechnology commercialization is based on the method of Delphi and AHP, there is a problem that it is difficult to have a generalization due to fluctuation results according to a pool of participants. Therefore, the purpose of the paper is to predict demand forecasting for identifying promising technology based on building up big data in medical biotechnology. The development method is to employ candidate technologies of keywords extracted from SCOPUS and to use word2vec for drawing analysis indicator, technological distance similarity, and recommended technological similarity of top-level items in order to achieve a reasonable result. In addition, the method builds up academic big data for 5 years (2016-2020) in order to commercialize technology excavation on demand perspective. Lastly, the paper employs global data studies in order to develop domestic and international demand for technology excavation in the medical biotechnology field.
Keywords
LOGREG; RF; KNN; SVM; LSTM; GRU; TFIDF; Medical; Biotechnology; Word2vec; Big data; ICT; AI; AHP; Delphi; SCOPUS; BT; NCBI; Pubmed;
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