18 November 2021 (Thursday) - "Good Morning Dave"...

The nice people at the American Society of Hematology sent another update today. I don’t post about many of their updates here as most of them aren’t really aimed at me, but one little snippet of this update made me think…
Much of what I do each day involves sitting at a microscope passing judgement on what I think I see down it. I think it fair to say I have a fair idea what I’m looking at. I think it fair to say that most people peering down them do. However there is still an awful lot of subjectivity involved. I can remember my first day on the microscope bench when one inexperienced trainee MLSO (as we were back then) found something she couldn’t identify in a blood film. What was that cell she saw? There were as many opinions as there were people to offer them.
And that is just in peripheral blood. Bone marrow is far more involved and examination of smears of that stuff requires serious experience.
 

Over the years flow cytometry has taken some of the guesswork out of the matter, and it would seem that neural networks are possibly the way forward

  • A data set of >170 000 microscopic images allows training neural networks for identification of BM cells with high accuracy.
     
  • Neural networks outperform a feature-based approach to BM cell classification and can be analyzed with explainability and feature embedding methods.
I bet they ain’t cheap… However I will comment that this sort of thing has been talked about for years and still hasn’t appeared in routine haematology labs

Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image data set

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