Automated quality control leverages AI that has been trained and tested on thousands of samples to identify commonly-occurring quality issues in every image of H&E stained slides. By reducing the need to manually review these images, it drives significant productivity and quality gains that may enable research teams to start studies faster, increase the reproducibility of results, and reduce technician burnout.
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October 1, 2024