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A new study from S:CORT demonstrates an easy, cheap way to determine colorectal cancer molecular subtype using AI deep-learning digital pathology technology.

Microscope and slide © Shutterstock

Understanding the molecular subtype of a cancer is becoming an importance part of the diagnostic process as it helps a doctor better understand a patient’s prognosis, determine the best course of action for treatment and helps researchers devise new, more-efficient, precision therapies.

Colorectal cancer (CRC) currently has four known molecular subtypes which are identified on the basis of its RNA expression profile, using RNA analysis. But the process of RNA analysis is costly, technically challenging and it requires a specialist to interpret data to determine the subtype. In order to more efficiently and cheaply determine the molecular subtype of a patient’s CRC, there is a need to use more easily-acquired data on a tumour and categorise its subtype based on an automated technique.

Read the full article (University of Oxford website)

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