The use of artificial intelligence in induced pluripotent stem cell-based technology over 10-year period: A systematic scoping review.

Journal: PloS one
PMID: 38771829

Abstract

BACKGROUND: Stem cell research, particularly in the domain of induced pluripotent stem cell (iPSC) technology, has shown significant progress. The integration of artificial intelligence (AI), especially machine learning (ML) and deep learning (DL), has played a pivotal role in refining iPSC classification, monitoring cell functionality, and conducting genetic analysis. These enhancements are broadening the applications of iPSC technology in disease modelling, drug screening, and regenerative medicine. This review aims to explore the role of AI in the advancement of iPSC research.

Authors

  • Quan Duy Vo
    Faculty of Medicine, Department of Cardiovascular Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
  • Yukihiro Saito
    Department of Cardiovascular Medicine, Okayama University Hospital, Okayama, Japan.
  • Toshihiro Ida
    Faculty of Medicine, Department of Cardiovascular Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
  • Kazufumi Nakamura
    Faculty of Medicine, Department of Cardiovascular Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
  • Shinsuke Yuasa
    Department of Cardiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan. Electronic address: yuasa@keio.jp.

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