Once outside the body, stored blood begins degrading until, by day 42, they're no longer usable. Until now, assessing its quality has required laborious microscopic examination by human experts. A new study reveals two methodologies that combine machine learning and state-of-the-art imaging to automate the process and eliminate human bias. If standardized, it could ensure more consistent, accurate assessments, with increased efficiency and better patient outcomes.
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Machines rival expert analysis of stored red blood cell quality
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