Quantification of tff3 expression from a non-endoscopic device predicts clinically relevant barrett`s oesophagus by machine learning

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  • who: Adam G. Berman from the Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK have published the research: Quantification of TFF3 expression from a non-endoscopic device predicts clinically relevant Barrett`s oesophagus by machine learning, in the Journal: (JOURNAL)
  • what: An automated prediction model can be used to accurately quantify the extent of IM from Cytosponge specimens without requiring the pathologist to perform a manual count and this model had a 90% precision for identifying focal IM pathologies. The aim of this study was to determine whether the TFF3 count generated by . . .

     

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