Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions

Shang Yuin Chai, Amjad Hayat, Gerard Thomas Flaherty

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

23 Citations (Scopus)

Abstract

There remains a limited emphasis on the use beyond the research domain of artificial intelligence (AI) in haematology and it does not feature significantly in postgraduate medical education and training. This perspective article considers recent developments in the field of AI research in haematology and anticipates the potential benefits and risks associated with its deeper integration into the specialty. Anxiety towards the greater use of AI in healthcare stems from legitimate concerns surrounding data protection, lack of transparency in clinical decision-making, and erosion of the doctor–patient relationship. The specialty of haematology has successfully embraced multiple disruptive innovations. We are at the cusp of a new era of closer integration of AI into routine haematology practice that will ultimately benefit patient care but to harness its benefits the next generation of haematologists will need access to bespoke learning opportunities with input from data scientists.

Original languageEnglish
Pages (from-to)807-811
Number of pages5
JournalBritish Journal of Haematology
Volume198
Issue number5
DOIs
Publication statusPublished - Sep 2022

Keywords

  • clinical decision support
  • haematological malignancies
  • haemoglobinopathies
  • machine learning
  • medical education
  • stem cell transplantation

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