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Korean Society of Medical Informatics, Healthcare Informatics Research, 2(28), p. 143-151, 2022

DOI: 10.4258/hir.2022.28.2.143

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Stakeholders’ Requirements for Artificial Intelligence for Healthcare in Korea

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
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Data provided by SHERPA/RoMEO

Abstract

Objectives: 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.Methods: 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).Results: 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.Conclusions: 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.