Identifying genomic subtypes of pancreatic cancer from histology slides using AI-based tool


Sumary of Identifying genomic subtypes of pancreatic cancer from histology slides using AI-based tool:

  • Demonstrates the first AI-based tool for predicting genomic subtypes of pancreatic cancer (PDAC) developed from machine learning applied to histology slides..
  • The tool, a trained and validated AI model, is usable in clinical practice worldwide and opens the possibility of patient molecular stratification in routine care and for clinical trials..
  • This study further underscores the value of using machine learning for identifying histo-genomic signals for cancer research and clinical development.”.
  • Improvement of prognosis has stalled while pancreatic cancer is predicted to become the second most lethal cancer by the year 2030..
  • The determination of these subtypes has been possible so far by RNA sequencing, a costly and complex technique that is not yet feasible in a clinical routine setting..
  • It can remotely subtype tumor in minutes paving the way for many applications from basic science (study of intra-tumor heterogeneity) to clinical practice (tumor subtyping in clinical trials).”.
  • Related Stories This research is born out of a successful and ongoing collaboration between Owkin’s multidisciplinary teams and those of the AP-HP Greater Paris University Hospitals..
  • Recently, in January 2021, AP-HP Greater Paris University Hospitals and Owkin published an AI-Severity score for Covid-19 patients using CT scans alongside other data modalities in Nature Communications….

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