Cargando…
Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions
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 haematolog...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9543760/ https://www.ncbi.nlm.nih.gov/pubmed/35781249 http://dx.doi.org/10.1111/bjh.18343 |
_version_ | 1784804449371291648 |
---|---|
author | Chai, Shang Yuin Hayat, Amjad Flaherty, Gerard Thomas |
author_facet | Chai, Shang Yuin Hayat, Amjad Flaherty, Gerard Thomas |
author_sort | Chai, Shang Yuin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9543760 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95437602022-10-14 Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions Chai, Shang Yuin Hayat, Amjad Flaherty, Gerard Thomas Br J Haematol Reviews 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. John Wiley and Sons Inc. 2022-07-04 2022-09 /pmc/articles/PMC9543760/ /pubmed/35781249 http://dx.doi.org/10.1111/bjh.18343 Text en © 2022 The Authors. British Journal of Haematology published by British Society for Haematology and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Reviews Chai, Shang Yuin Hayat, Amjad Flaherty, Gerard Thomas Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions |
title | Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions |
title_full | Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions |
title_fullStr | Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions |
title_full_unstemmed | Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions |
title_short | Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions |
title_sort | integrating artificial intelligence into haematology training and practice: opportunities, threats and proposed solutions |
topic | Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9543760/ https://www.ncbi.nlm.nih.gov/pubmed/35781249 http://dx.doi.org/10.1111/bjh.18343 |
work_keys_str_mv | AT chaishangyuin integratingartificialintelligenceintohaematologytrainingandpracticeopportunitiesthreatsandproposedsolutions AT hayatamjad integratingartificialintelligenceintohaematologytrainingandpracticeopportunitiesthreatsandproposedsolutions AT flahertygerardthomas integratingartificialintelligenceintohaematologytrainingandpracticeopportunitiesthreatsandproposedsolutions |