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Mount Sinai Team Publishes MARQO, AI Pipeline for Faster Whole-Slide Cancer Tissue Analysis

The research-only pipeline converts intact whole-slide histology into structured cellular and spatial data within minutes.

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Overview

  • The peer-reviewed study introducing MARQO appears in Nature Biomedical Engineering from a team led by Sacha Gnjatic, PhD.
  • MARQO processes entire tumor slides without patching and completes analyses in minutes on standard GPUs.
  • The system supports common immunohistochemistry and immunofluorescence staining technologies to improve cross-study reproducibility.
  • It automatically flags likely positive cells with recorded coordinates and marker intensities, leaving final validation to pathologists.
  • The developers plan user interface upgrades, advanced spatial and neighborhood analyses, and high-performance computing scaling, and they note MARQO is for research use only and not validated for clinical diagnostics.