Nasir Rajpoot

This paper shows that deep learning models for predicting biomarkers from histology images are confounded by interdependencies among biomarkers, leading to less accurate and less reliable predictions.

ShapeSpaceExplorer analyzes morphological transitions in migrating cells using a shape difference measure to visualize and quantify shape changes during migration.

Star-Motifs identifies spatial patterns in histology slides to reveal clinically relevant tumor microenvironment features and survival correlations.

This paper develops a deep learning framework to predict consensus molecular subtypes in HPV-positive cervical cancer from histology images, showing significant survival stratification and TME differences between subtypes.