Ann Lab Med.  2024 Nov;44(6):562-571. 10.3343/alm.2024.0111.

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

Affiliations
  • 1Department of Laboratory Medicine, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
  • 2Department of Laboratory Medicine & Genetics, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon, Korea
  • 3Departments of Laboratory Medicine, Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung, Korea
  • 4Department of Laboratory Medicine and Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, Korea
  • 5Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
  • 6Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
  • 7Department of Laboratory Medicine, Inje University College of Medicine, Busan, Korea; 8 Department of Laboratory Medicine, GC Labs, Yongin, Korea
  • 8Department of Laboratory Medicine, Chungnam National University Sejong Hospital, Chungnam National University School of Medicine, Daejeon, Korea
  • 9Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
  • 10Department of Laboratory Medicine, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Korea
  • 11Department of Laboratory Medicine, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Korea

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. Thirtytwo 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.

Keyword

Artificial intelligence; Big data; Digital medicine; Healthcare 4.0; Laboratory medicine

Figure

  • Fig. 1 Most important technologies introduced in LM with the advent of Healthcare 4.0. Abbreviations: AI, artificial intelligence; AR, augmented reality; VR, virtual reality; IoT, internet of things; 3D, three-dimensional; LM, laboratory medicine.

  • Fig. 2 Statistical software (A) and programming languages (B) used in big data analysis.

  • Fig. 3 LM division in which AI is considered to be the most useful for laboratory work. Abbreviations: LM, laboratory medicine; AI, artificial intelligence.


Reference

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