John V. Heymach

12 papers Journal 8Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
From classical machine learning to emerging foundation models: review on multimodal data integration for cancer research.
Artif. Intell. Rev.
Amgad Muneer, Muhammad Waqas, Maliazurina B. Saad, Eman Showkatian, Rukhmini Bandyopadhyay, Hui Xu, Wentao Li, Joe Y. Chang, Zhongxing Liao, Cara Haymaker, Luisa Solis-Soto, Carol C. Wu, Natalie I. Vokes, Xiuning Le, Lauren A. Byers, Don L. Gibbons, John V. Heymach, Jianjun Zhang, Jia Wu
2025 J jnl
From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research.
CoRR
Amgad Muneer, Muhammad Waqas, Maliazurina B. Saad, Eman Showkatian, Rukhmini Bandyopadhyay, Hui Xu, Wentao Li, Joe Y. Chang, Zhongxing Liao, Cara Haymaker, Luisa Solis-Soto, Carol C. Wu, Natalie I. Vokes, Xiuning Le, Lauren A. Byers, Don L. Gibbons, John V. Heymach, Jianjun Zhang, Jia Wu
2025 J jnl
The Next Layer: Augmenting Foundation Models with Structure-Preserving and Attention-Guided Learning for Local Patches to Global Context Awareness in Computational Pathology.
CoRR
Muhammad Waqas, Rukhmini Bandyopadhyay, Eman Showkatian, Amgad Muneer, Anas Zafar, Frank Rojas Alvarez, Maricel Corredor Marin, Wentao Li, David A. Jaffray, Cara Haymaker, John V. Heymach, Natalie I. Vokes, Luisa M. Solis Soto, Jianjun Zhang, Jia Wu
2024 — conf
Estimating the Average Treatment Effect Using Weighting Methods in Lung Cancer Immunotherapy.
CMMCA@MICCAI
Maliazurina B. Saad, Qasem Al-Tashi, Lingzhi Hong, Wentao Li, Shenduo Li, John V. Heymach, Yanyan Lou, Natalie I. Vokes, Jianjun Zhang, Jia Wu
2024 — conf
PD-L1 Expression Prediction Using Scalable Multi Instance Transformer.
CMMCA@MICCAI
Eman Showkatian, Amgad Muneer, Maliazurina B. Saad, Lingzhi Hong, John V. Heymach, Jianjun Zhang, Jia Wu
2023 J jnl
A novel statistical method for decontaminating T-cell receptor sequencing data.
Briefings Bioinform.
Ruoxing Li, Mehmet Altan, Alexandre Reuben, Ruitao Lin, John V. Heymach, Hai Tran, Runzhe Chen, Latasha Little, Shawna Hubert, Jianjun Zhang, Ziyi Li
2023 J jnl
SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers.
Patterns
Qasem Al-Tashi, Maliazurina B. Saad, Ajay Sheshadri, Carol C. Wu, Joe Y. Chang, Bissan Al-Lazikani, Christopher Gibbons, Natalie I. Vokes, Jianjun Zhang, J. Jack Lee, John V. Heymach, David A. Jaffray, Seyedali Mirjalili, Jia Wu
2022 — conf
Cellular Architecture on Whole Slide Images Allows the Prediction of Survival in Lung Adenocarcinoma.
CMMCA@MICCAI
Pingjun Chen, Maliazurina B. Saad, Frank R. Rojas, Morteza Salehjahromi, Muhammad Aminu, Rukhmini Bandyopadhyay, Lingzhi Hong, Kingsley Ebare, Carmen Behrens, Don L. Gibbons, Neda Kalhor, John V. Heymach, Ignacio I. Wistuba, Luisa M. Solis Soto, Jianjun Zhang, Jia Wu
2021 J jnl
Deep learning-based prediction of the T cell receptor-antigen binding specificity.
Nat. Mach. Intell.
Tianshi Lu, Ze Zhang, James Zhu, Yunguan Wang, Peixin Jiang, Xue Xiao, Chantale Bernatchez, John V. Heymach, Don L. Gibbons, Jun Wang, Lin Xu, Alexandre Reuben, Tao Wang
2021 J jnl
Radiological tumour classification across imaging modality and histology.
Nat. Mach. Intell.
Jia Wu, Chao Li, Michael Gensheimer, Sukhmani Padda, Fumi Kato, Hiroki Shirato, Yiran Wei, Carola-Bibiane Schönlieb, Stephen John Price, David A. Jaffray, John V. Heymach, Joel W. Neal, Billy W. Loo, Heather Wakelee, Maximilian Diehn, Ruijiang Li
2015 J jnl
drexplorer: A tool to explore dose-response relationships and drug-drug interactions.
Bioinform.
Pan Tong, Kevin R. Coombes, Faye M. Johnson, Lauren A. Byers, Lixia Diao, Diane D. Liu, J. Jack Lee, John V. Heymach, Jing Wang
2012 — conf
Latent feature decompositions for integrative analysis of diverse high-throughput genomic data.
GENSiPS
Karl B. Gregory, Kevin R. Coombes, Amin A. Momin, Luc Girard, Lauren A. Byers, Steven Lin, Michael Peyton, John V. Heymach, John D. Minna, Veerabhadran Baladandayuthapani