David J. Harrison

According to our database, David J. Harrison authored at least 14 papers between 2012 and 2024.

Collaborative distances:

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

2024

Leveraging Foundation Models for Enhanced Detection of Colorectal Cancer Biomarkers in Small Datasets.

Craig Myles, In Hwa Um, David J. Harrison, David Harris-Birtill

Proceedings of the Medical Image Understanding and Analysis - 28th Annual Conference, 2024

2023

Whole-Slide Images and Patches of Clear Cell Renal Cell Carcinoma Tissue Sections Counterstained with Hoechst 33342, CD3, and CD8 Using Multiple Immunofluorescence.

Georg Wölflein, In Hwa Um, David J. Harrison, Ognjen Arandjelovic

Data, February, 2023

A Good Feature Extractor Is All You Need for Weakly Supervised Learning in Histopathology.

Georg Wölflein, Dyke Ferber, Asier Rabasco Meneghetti, Omar S. M. El Nahhas, Daniel Truhn, Zunamys I. Carrero, David J. Harrison, Ognjen Arandjelovic, Jakob Nikolas Kather

CoRR, 2023

Deep Multiple Instance Learning with Distance-Aware Self-Attention.

Georg Wölflein, Lucie Charlotte Magister, Pietro Liò, David J. Harrison, Ognjen Arandjelovic

CoRR, 2023

HoechstGAN: Virtual Lymphocyte Staining Using Generative Adversarial Networks.

Georg Wölflein, In Hwa Um, David J. Harrison, Ognjen Arandjelovic

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

MultiPathGAN: Structure Preserving Stain Normalization using Unsupervised Multi-domain Adversarial Network with Perception Loss.

Haseeb Nazki, Ognjen Arandjelovic, In Hwa Um, David J. Harrison

Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023

2022

Believe the HiPe: Hierarchical perturbation for fast, robust, and model-agnostic saliency mapping.

Jessica Cooper, Ognjen Arandjelovic, David J. Harrison

Pattern Recognit., 2022

2021

Hoechst Is All You Need: Lymphocyte Classification with Deep Learning.

Jessica Cooper, In Hwa Um, Ognjen Arandjelovic, David J. Harrison

CoRR, 2021

Believe The HiPe: Hierarchical Perturbation for Fast and Robust Explanation of Black Box Models.

Jessica Cooper, Ognjen Arandjelovic, David J. Harrison

CoRR, 2021

2020

Spatial immune profiling of the colorectal tumor microenvironment predicts good outcome in stage II patients.

Ines P. Nearchou, Bethany M. Gwyther, Elena C. T. Georgiakakis, Christos G. Gavriel, Kate Lillard, Yoshiki Kajiwara, Hideki Ueno, David J. Harrison, Peter D. Caie

npj Digit. Medicine, 2020

2018

A principled machine learning framework improves accuracy of stage II colorectal cancer prognosis.

Neofytos Dimitriou, Ognjen Arandjelovic, David J. Harrison, Peter D. Caie

npj Digit. Medicine, 2018

Context-based interpolation of coarse deep learning prediction maps for the segmentation of fine structures in immunofluorescence images.

Nicolas Brieu, Christos G. Gavriel, David J. Harrison, Peter D. Caie, Günter Schmidt

Proceedings of the Medical Imaging 2018: Digital Pathology, 2018

2013

TMA Navigator: network inference, patient stratification and survival analysis with tissue microarray data.

Alexander L. R. Lubbock, Elad Katz, David J. Harrison, Ian M. Overton

Nucleic Acids Res., 2013

2012

A model of estrogen-related gene expression reveals non-linear effects in transcriptional response to tamoxifen.

Galina Lebedeva, Azusa Yamaguchi, Simon P. Langdon, Kenneth Macleod, David J. Harrison

BMC Syst. Biol., 2012