Predicting Mechanical Ventilation Requirement and Mortality in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study. - Joseph Bae; Saarthak Kapse; Gagandeep Singh; Tej Phatak; Jeremy Green; Nikhil Madan; Prateek Prasanna (CoRR, 2020)

TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer. - Fan Wang 010; Saarthak Kapse; Steven Liu; Prateek Prasanna; Chao Chen 012 (IPMI, 2021)

Subtype-Specific Spatial Descriptors of Tumor-Immune Microenvironment are Prognostic of Survival in Lung Adenocarcinoma. - Saarthak Kapse; Luke Torre-Healy; Richard A. Moffitt; Rajarsi Gupta 001; Prateek Prasanna (ISBI, 2022)

Shape-based tumor microenvironment analysis to differentiate non-small cell lung cancer subtypes: a radio-pathomic study. - Saarthak Kapse; Rajarsi Gupta 001; Prateek Prasanna (Digital and Computational Pathology, 2022)

CD-Net: Histopathology Representation Learning using Pyramidal Context-Detail Network. - Saarthak Kapse; Srijan Das; Prateek Prasanna (CoRR, 2022)

Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology. - Jingwei Zhang; Saarthak Kapse; Ke Ma 005; Prateek Prasanna; Maria Vakalopoulou; Joel H. Saltz; Dimitris Samaras (IPMI, 2023)

CD-Net: Histopathology Representation Learning Using Context-Detail Transformer Network. - Saarthak Kapse; Srijan Das; Prateek Prasanna (ISBI, 2023)

ViT-DAE: Transformer-Driven Diffusion Autoencoder for Histopathology Image Analysis. - Xuan Xu; Saarthak Kapse; Rajarsi Gupta 001; Prateek Prasanna (DGM4MICCAI, 2023)

Prompt-MIL: Boosting Multi-instance Learning Schemes via Task-Specific Prompt Tuning. - Jingwei Zhang; Saarthak Kapse; Ke Ma 005; Prateek Prasanna; Joel H. Saltz; Maria Vakalopoulou; Dimitris Samaras (MICCAI (8), 2023)

SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology. - Jingwei Zhang; Ke Ma 005; Saarthak Kapse; Joel H. Saltz; Maria Vakalopoulou; Prateek Prasanna; Dimitris Samaras (ISIC/Care-AI/MedAGI/DeCaF@MICCAI, 2023)

Role of stain normalization in computational pathology: use case in metastatic tissue classification. - Paras Goel; Saarthak Kapse; Prateek Prasanna (Digital and Computational Pathology, 2023)

Learned Representation-Guided Diffusion Models for Large-Image Generation. - Alexandros Graikos; Srikar Yellapragada; Minh-Quan Le; Saarthak Kapse; Prateek Prasanna; Joel H. Saltz; Dimitris Samaras (CVPR, 2024)

SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology. - Saarthak Kapse; Pushpak Pati; Srijan Das; Jingwei Zhang; Chao Chen 012; Maria Vakalopoulou; Joel H. Saltz; Dimitris Samaras; Rajarsi R. Gupta; Prateek Prasanna (CVPR, 2024)

Coca-Mil: Attention-Based Handcrafted-Deep Feature Fusion in Computational Pathology. - Paras Goel; Saarthak Kapse; Pushpak Pati; Prateek Prasanna (ISBI, 2024)

HoG-Net: Hierarchical Multi-organ Graph Network for Head and Neck Cancer Recurrence Prediction from CT Images. - Joseph Bae; Saarthak Kapse; Lei Zhou; Kartik Mani; Prateek Prasanna (MICCAI (5), 2024)

Histo-Diffusion: A Diffusion Super-Resolution Method for Digital Pathology with Comprehensive Quality Assessment. - Xuan Xu; Saarthak Kapse; Prateek Prasanna (CoRR, 2024)

RankByGene: Gene-Guided Histopathology Representation Learning Through Cross-Modal Ranking Consistency. - Wentao Huang; Meilong Xu; Xiaoling Hu 002; Shahira Abousamra; Aniruddha Ganguly; Saarthak Kapse; Alisa Yurovsky; Prateek Prasanna; Tahsin M. Kurç; Joel H. Saltz; Michael L. Miller; Chao Chen 012 (CoRR, 2024)

Gen-SIS: Generative Self-augmentation Improves Self-supervised Learning. - Varun Belagali; Srikar Yellapragada; Alexandros Graikos; Saarthak Kapse; Zilinghan Li; Tarak Nath Nandi; Ravi K. Madduri; Prateek Prasanna; Joel H. Saltz; Dimitris Samaras (CoRR, 2024)

Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning. - Saarthak Kapse; Srijan Das; Jingwei Zhang; Rajarsi R. Gupta; Joel H. Saltz; Dimitris Samaras; Prateek Prasanna (Medical Image Anal., 2024)

Fast Vision Mamba: Pooling Spatial Dimensions for Accelerated Processing. - Saarthak Kapse; Robin Betz; Srinivasan Sivanandan (CoRR, 2025)

GECKO: Gigapixel Vision-Concept Contrastive Pretraining in Histopathology. - Saarthak Kapse; Pushpak Pati; Srikar Yellapragada; Srijan Das; Rajarsi R. Gupta; Joel H. Saltz; Dimitris Samaras; Prateek Prasanna (CoRR, 2025)

PixCell: A generative foundation model for digital histopathology images. - Srikar Yellapragada; Alexandros Graikos; Zilinghan Li; Kostas Triaridis; Varun Belagali; Saarthak Kapse; Tarak Nath Nandi; Ravi K. Madduri; Prateek Prasanna; Tahsin M. Kurç; Rajarsi R. Gupta; Joel H. Saltz; et al. (CoRR, 2025)