Article published in npj Digital Medicine

Our paper on Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations, by Niccolò Marini et al., has been published in npj Digital Medicine and is available in open access.

This work presents an approach that removes the need for human experts to annotate data, using an automatic analysis of healthcare reports to create automatic annotations that can be used to train deep learning models. A case study on the classification of colon whole slide images shows the benefit of the approach to best exploit the potential of healthcare data from hospital workflows.

a Input data from the clinical workflow. b Image Classification pipeline c The textual report pipeline automatically analyzes pathologist reports, to identify meaningful concepts to be used as weak labels for the CNN.