Artificial Intelligence for Digital Pathology

Digital pathology is an emerging sub-division of conventional microscopy, enabling practitioners to virtualize glass pathology slides for more in-depth analysis.

Artificial intelligence algorithms can assist pathologists with:

  • Image analysis and interpretation
  • Detailed inspections of sample tissues
  • Pathology types matching to earlier cases
  • Diagnosis accuracy and early detection

A group of cancer researchers recently analyzed a public database of WSIs from 11,000 cancer patients, featuring 32 cancer subtypes. The trained algorithm leveraged image data and annotations to reach a “computational consensus” on the type of pathology on display.  The tool identified different types of pathology on frozen section slides with high accuracy:

  • 93% for bladder urothelial carcinoma
  • 97% for kidney renal clear cell carcinoma
  • 99% for ovarian serous cystadenocarcinoma

And performed equally accurately with histopathology slides:

  • 98% for prostate adenocarcinoma
  • 99% for skin cutaneous melanoma
  • 100% for thymoma


Similar artificial intelligence tools can support clinical decision-making and enhance the diagnosis of lesser studied pathologies and early-stage variations.