1 citations · 1 across the 10 of their papers we have counts for
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PEaRL: Pathway-Enhanced Representation Learning for Gene and Pathway Expression Prediction from Histology
Sejuti Majumder, Saarthak Kapse, Moinak Bhattacharya +3
Integrating histopathology with spatial transcriptomics (ST) provides a powerful opportunity to link tissue morphology with molecular function. Yet most existing multimodal approac…
SoC-DT: Standard-of-Care Aligned Digital Twins for Patient-Specific Tumor Dynamics
Moinak Bhattacharya, Gagandeep Singh, Prateek Prasanna
Accurate prediction of tumor trajectories under standard-of-care (SoC) therapies remains a major unmet need in oncology. This capability is essential for optimizing treatment plann…
NeuroRAD-FM: A Foundation Model for Neuro-Oncology with Distributionally Robust Training
Moinak Bhattacharya, Angelica P. Kurtz, Fabio M. Iwamoto +2
Neuro-oncology poses unique challenges for machine learning due to heterogeneous data and tumor complexity, limiting the ability of foundation models (FMs) to generalize across coh…
GazeLT: Visual attention-guided long-tailed disease classification in chest radiographs
Moinak Bhattacharya, Gagandeep Singh, Shubham Jain +1
In this work, we present GazeLT, a human visual attention integration-disintegration approach for long-tailed disease classification. A radiologist's eye gaze has distinct patterns…