All content on this site is intended for healthcare professionals only. By acknowledging this message and accessing the information on this website you are confirming that you are a Healthcare Professional. If you are a patient or carer, please visit the MPN Advocates Network.
The MPN Hub uses cookies on this website. They help us give you the best online experience. By continuing to use our website without changing your cookie settings, you agree to our use of cookies in accordance with our updated Cookie Policy
Introducing
Now you can personalise
your MPN Hub experience!
Bookmark content to read later
Select your specific areas of interest
View content recommended for you
Find out moreThe MPN Hub website uses a third-party service provided by Google that dynamically translates web content. Translations are machine generated, so may not be an exact or complete translation, and the MPN Hub cannot guarantee the accuracy of translated content. The MPN Hub and its employees will not be liable for any direct, indirect, or consequential damages (even if foreseeable) resulting from use of the Google Translate feature. For further support with Google Translate, visit Google Translate Help.
The MPN Hub is an independent medical education platform, sponsored by AOP Health and GSK, and supported through an educational grant from Bristol Myers Squibb. The funders are allowed no direct influence on our content. The levels of sponsorship listed are reflective of the amount of funding given. View funders.
The role of AI in the future of MPN bone marrow histopathology
Bookmark this article
The MPN Hub invited Daniel Royston, University of Oxford, UK, to give a presentation and chair a discussion on the role of artificial intelligence in the future of myeloproliferative neoplasm bone marrow histopathology. MPN Hub Steering Committee members Jean-Jacques Kiladjian, Tiziano Barbui, Chloe James, and John Mascarenhas joined the discussion.
Royston begins by describing quantitative image analysis in myeloproliferative neoplasms and its potential in clinical trial scenarios. He then outlines results of a quantitative analysis of fibrosis from the zinpentraxin alfa phase II study (NCT01981850). He concludes by highlighting a need for the clinical evaluation and validation of machine learning tools in histopathology.
The role of AI in the future of MPN bone marrow histopathology
Related articles
Newsletter
Subscribe to get the best content related to MPN delivered to your inbox