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Performance of an artificial intelligence algorithm for reporting urine cytopathology.

Adit B SanghviErastus Z AllenKeith M CallenbergLiron Pantanowitz
Published in: Cancer cytopathology (2019)
The authors successfully developed a computational algorithm capable of accurately analyzing WSIs of urine cytology cases. Compared with prior studies, this effort used a much larger data set, exploited whole slide-level and not just cell-level features, and used a cell gallery to display the algorithm's output for easy end-user review. This algorithm provides computer-assisted interpretation of urine cytology cases, akin to the machine learning technology currently used for automated Papanicolaou test screening.
Keyphrases
  • machine learning
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  • fine needle aspiration
  • single cell
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  • cell therapy
  • stem cells
  • high throughput
  • adverse drug