Artificial Intelligence for Prostate Cancer Diagnosis and Prognostication

SNIC 2022/23-260


SNIC Small Storage

Principal Investigator:

Martin Eklund


Karolinska Institutet

Start Date:


End Date:


Primary Classification:

30203: Cancer and Oncology




Digital pathology enables using AI for improved cancer diagnostics and ultimately better treatment decisions. We will develop a prognostic AI system for prostate cancer pathology by integrating: 1) Large-scale datasets of digitized prostate biopsies from a network of health care providers, 2) Cohorts with follow-up for clinical outcomes; and 3) Genomic profiling of the samples. This will allow extending prognostication beyond human capacity by directly predicting disease progress from images and by integrating molecular data with tissue morphology. Utilizing diverse international data will allow training robust models and evaluating them in view of real-world sources of variation. We will utilize the capacity of SNIC Alvis by posing the project as an automated machine learning problem to design the system in a data-driven manner. This novel way of solving problems in computational pathology complements the major clinical significance of the project with potential for technological advances.