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Stakeholders' Requirements for Artificial Intelligence for Healthcare in Korea.

Authors
  • Yu, Jae Yong1
  • Hong, Sungjun1
  • Lee, Yeong Chan1
  • Lee, Kyung Hyun1
  • Lee, Ildong1
  • Seo, Yeoni2
  • Kang, Mira1, 3
  • Kim, Kyunga1, 4
  • Cha, Won Chul1, 5, 6
  • Shin, Soo-Yong1, 6, 7
  • 1 Department of Digital Health, Samsung Advanced Institute of Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea. , (North Korea)
  • 2 Department of International Health and Health Policy, Clinical & Public Health Convergence, Ewha Womans University, Seoul, Korea. , (North Korea)
  • 3 Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. , (North Korea)
  • 4 Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea. , (North Korea)
  • 5 Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. , (North Korea)
  • 6 Digital Innovation Center, Samsung Medical Center, Seoul, Korea. , (North Korea)
  • 7 Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea. , (North Korea)
Type
Published Article
Journal
Healthcare informatics research
Publication Date
Apr 01, 2022
Volume
28
Issue
2
Pages
143–151
Identifiers
DOI: 10.4258/hir.2022.28.2.143
PMID: 35576982
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

The outlook of artificial intelligence for healthcare (AI4H) is promising. However, no studies have yet discussed the issues from the perspective of stakeholders in Korea. This research aimed to identify stakeholders' requirements for AI4H to accelerate the business and research of AI4H. We identified research funding trends from the Korean National Science and Technology Knowledge Information Service (NTIS) from 2015 and 2019 using "healthcare AI" and related keywords. Furthermore, we conducted an online survey with members of the Korean Society of Artificial Intelligence in Medicine to identify experts' opinions regarding the development of AI4H. Finally, expert interviews were conducted with 13 experts in three areas (hospitals, industry, and academia). We found 160 related projects from the NTIS. The major data type was radiology images (59.4%). Dermatology-related diseases received the most funding, followed by pulmonary diseases. Based on the survey responses, radiology images (23.9%) were the most demanding data type. Over half of the solutions were related to diagnosis (33.3%) or prognosis prediction (31%). In the expert interviews, all experts mentioned healthcare data for AI solutions as a major issue. Experts in the industrial field mainly mentioned regulations, practical efficacy evaluation, and data accessibility. We identified technology, regulatory, and data issues for practical AI4H applications from the perspectives of stakeholders in hospitals, industry, and academia in Korea. We found issues and requirements, including regulations, data utilization, reimbursement, and human resource development, that should be addressed to promote further research in AI4H.

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