New AI Tools Aim to Identify Tissue Samples at Risk of Failed Molecular Testing
clpmag.comClinical Lab Products
AI tools are being developed to assess tissue sample quality before molecular testing, potentially reducing failed diagnostic procedures in pathology laboratories. These systems aim to identify problematic samples early in the diagnostic workflow.
Why it mattersFailed molecular tests delay cancer diagnoses and require expensive re-sampling; pre-screening tools could save laboratories time and costs while improving patient outcomes by catching quality issues upfront.
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