Original Article2024-11-01 Laboratory Informatics

Laboratory Preparation for Digital Medicine in Healthcare 4.0: An Investigation Into the Awareness and Applications of Big Data and Artificial Intelligence

Shinae Yu , M.D., Byung Ryul Jeon , M.D., Ph.D., Changseung Liu , M.D., Dokyun Kim , M.D., Ph.D., Hae-Il Park , M.D., Ph.D., Hyung Doo Park , M.D., Ph.D., Jeong Hwan Shin , M.D., Ph.D., Jun Hyung Lee , M.D., Ph.D., Qute Choi , M.D., Ph.D., Sollip Kim , M.D., Ph.D., Yeo Min Yun , M.D., Ph.D., and Eun-Jung Cho , M.D., Ph.D.; On behalf of the Evidence-Based Laboratory Medicine Committee of the Korean Society for Laboratory Medicine

Ann Lab Med 2024; 44(6): 562-571

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Abstract : Background: Healthcare 4.0. refers to the integration of advanced technologies, such as artificial intelligence (AI) and big data analysis, into the healthcare sector. Recognizing the impact of Healthcare 4.0 technologies in laboratory medicine (LM), we seek to assess the overall awareness and implementation of Healthcare 4.0 among members of the Korean Society for Laboratory Medicine (KSLM).Methods: A web-based survey was conducted using an anonymous questionnaire. The survey comprised 36 questions covering demographic information (seven questions), big data (10 questions), and AI (19 questions).Results: In total, 182 (17.9%) of 1,017 KSLM members participated in the survey. Thirty-two percent of respondents considered AI to be the most important technology in LM in the era of Healthcare 4.0, closely followed by 31% who favored big data. Approximately 80% of respondents were familiar with big data but had not conducted research using it, and 71% were willing to participate in future big data research conducted by the KSLM. Respondents viewed AI as the most valuable tool in molecular genetics within various divisions. More than half of the respondents were open to the notion of using AI as assistance rather than a complete replacement for their roles.Conclusions: This survey highlighted KSLM members’ awareness of the potential applications and implications of big data and AI. We emphasize the complexity of AI integration in healthcare, citing technical and ethical challenges leading to diverse opinions on its impact on employment and training. This highlights the need for a holistic approach to adopting new technologies.

Opinion2024-11-01 Laboratory Informatics

Why Terminology Standards Matter for Data-driven Artificial Intelligence in Healthcare

Hyeoun-Ae Park , Ph.D.

Ann Lab Med 2024; 44(6): 467-471

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Opinion2024-11-01 Laboratory Informatics

Customized Quality Assessment of Healthcare Data

Jieun Shin , Ph.D. and Jong-Yeup Kim , M.D., Ph.D.

Ann Lab Med 2024; 44(6): 472-477

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