Kai Rakovic

This study identifies Podocalyxin as a regulator of glandular architecture in colorectal cancer, showing its role in promoting tumour growth and metastasis.

This study identifies architectural subtypes of PDAC using morphospatial profiling of CAFs, showing improved prognostication and chemotherapy response prediction.

This paper uses self-supervised AI to identify under-appreciated stromal morphologies in lung adenocarcinoma linked to poor prognosis, independent of current clinical schemas.

This paper introduces a self-supervised learning framework to analyze multiplex immunofluorescence images, revealing novel prognostic spatial patterns in cancer tissues.

This paper uses self-supervised learning on 3446 H&E-stained mesothelioma slides to create a histomorphological atlas, achieving high predictive performance and revealing molecular insights.

PixlMap is a deep learning method for cellular phenotyping in multiplex immunofluorescence images that uses nuclear segmentation alone to classify cells without requiring full cell boundaries.