John V. Heymach

According to our database, John V. Heymach authored at least 7 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers.

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

Patterns, August, 2023

A novel statistical method for decontaminating T-cell receptor sequencing data.

Ruoxing Li, Mehmet Altan, Alexandre Reuben, Ruitao Lin, John V. Heymach, Hai Tran, Runzhe Chen, Latasha Little, Shawna Hubert, Jianjun Zhang, Ziyi Li

Briefings Bioinform., July, 2023

2022

Cellular Architecture on Whole Slide Images Allows the Prediction of Survival in Lung Adenocarcinoma.

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

Proceedings of the Computational Mathematics Modeling in Cancer Analysis, 2022

2021

Radiological tumour classification across imaging modality and histology.

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

Nat. Mach. Intell., 2021

Deep learning-based prediction of the T cell receptor-antigen binding specificity.

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

Nat. Mach. Intell., 2021

2015

drexplorer: A tool to explore dose-response relationships and drug-drug interactions.

Pan Tong, Kevin R. Coombes, Faye M. Johnson, Lauren A. Byers, Lixia Diao, Diane D. Liu, J. Jack Lee, John V. Heymach, Jing Wang

Bioinform., 2015

2012

Latent feature decompositions for integrative analysis of diverse high-throughput genomic data.

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

Proceedings of the Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, 2012