Korean Journal of Artificial Intelligence (한국인공지능학회지)

Korea Artificial Intelligence Association (한국인공지능학회)
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Analysis of the Status of Artificial Medical Intelligence Technology Based on Big Data

  • KIM, Kyung-A (Department of Medical Artificial Intelligence, Eulji University) ;
  • CHUNG, Myung-Ae (Department of BigData Medical Convergence, Eulji University)
  • Received : 2022.09.01
  • Accepted : 2022.10.28
  • Published : 2022.12.30
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Abstract

The role of artificial medical intelligence through medical big data has been focused on data-based medical device business and medical service technology development in the field of diagnostic examination of the patient's current condition, clinical decision support, and patient monitoring and management. Recently, with the 4th Industrial Revolution, the medical field changed the medical treatment paradigm from the method of treatment based on the knowledge and experience of doctors in the past to the form of receiving the help of high-precision medical intelligence based on medical data. In addition, due to the spread of non-face-to-face treatment due to the COVID-19 pandemic, it is expected that the era of telemedicine, in which patients will be treated by doctors at home rather than hospitals, will soon come. It can be said that artificial medical intelligence plays a big role at the center of this paradigm shift in prevention-centered treatment rather than treatment. Based on big data, this paper analyzes the current status of artificial intelligence technology for chronic disease patients, market trends, and domestic and foreign company trends to predict the expected effect and future development direction of artificial intelligence technology for chronic disease patients. In addition, it is intended to present the necessity of developing digital therapeutics that can provide various medical services to chronically ill patients and serve as medical support to clinicians.

Keywords

Acknowledgement

This paper was supported by IITP(Institute of Information & Communications Technology Planning & Evaluation(www.iitp.kr). Foundation funded by the Ministry of Science and ICT(MSIT, Korea). [Project Number: 2022-00317]. This paper was supported by the research grant of the KODISA scholarship foundation in 2022.

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