By Dr Jitendra Jonnagaddala

Preprints

Cen M; Li X; Guo B; Jonnagaddala J; Zhang H; Xu XS, 2023, DPSeq: A Novel and Efficient Digital Pathology Classifier for Predicting Cancer Biomarkers using Sequencer Architecture, , http://dx.doi.org/10.48550/arxiv.2305.01968

Cen M; Li X; Guo B; Jonnagaddala J; Zhang H; Xu XS, 2023, Time to Embrace Natural Language Processing (NLP)-based Digital Pathology: Benchmarking NLP- and Convolutional Neural Network-based Deep Learning Pipelines, , http://dx.doi.org/10.48550/arxiv.2302.10406

Liu A; Li X; Wu H; Guo B; Jonnagaddala J; Zhang H; Xu XS, 2022, Prognostic Significance of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images in Colorectal Cancers, , http://dx.doi.org/10.48550/arxiv.2208.11518

Guo B; Li X; Jonnagaddala J; Zhang H; Xu XS, 2022, Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E-stained images: Achieving SOTA predictive performance with fewer data using Swin Transformer, , http://dx.doi.org/10.48550/arxiv.2208.10495

Li X; Jonnagaddala J; Cen M; Zhang H; Xu XS, 2022, Colorectal cancer survival prediction using deep distribution based multiple-instance learning, , http://dx.doi.org/10.48550/arxiv.2204.11294

Banda JM; Adderley N; Ahmed W-U-R; AlGhoul H; Alser O; Alser M; Areia C; Cogenur M; Fišter K; Gombar S; Huser V; Jonnagaddala J; Lai LYH; Leis A; Mateu L; Mayer MA; Minty E; Morales D; Natarajan K; Paredes R; Periyakoil VS; Prats-Uribe A; Ross EG; Singh G; Subbian V; Vivekanantham A; Prieto-Alhambra D, 2021, Characterization of long-term patient-reported symptoms of COVID-19: an analysis of social media data, , http://dx.doi.org/10.1101/2021.07.13.21260449

Back to profile page