Computational Pathology

Computational pathology is a brand-new discipline that aims to enhance patient care by utilizing advances in artificial intelligence and data generated from anatomic and clinical pathology.  This can be achieved by transforming the practice of pathology into a multi-omics field that integrates all levels of data from patient demographics and epidemiology to imaging studies to tissue - all the way down to the molecular level.

Further enabling computational pathology is the recent advances in computerized quantification and classification of tissue morphology, a task that has traditionally been performed manually using a microscope since the dawn of the field.  We believe pathologists and laboratory medicine professionals must lead the effort to advance computational pathology and ensure patient care as the main focus.

Empowered by machine learning and artificial intelligence, computational pathology can:

  • generate more precise diagnoses
  • add to the discovery of new clinically relevant patterns of injury
  • expand the recognition of pathologic changes beyond the limits of conventional visual light microscopic assessment
  • lead to a better understanding of the structural underpinnings of diseases
  • improve patient care!

If we examine the trend of precision medicine, we are no longer simply drinking water from a firehose – we are drowning in an exponentially expanding sea of information. The proposition of computational pathology and augmented intelligence is not optional, it is the only way forward

Dr. Daniel Qazi, Resident

University of California San Francisco