Search results (7)
« Back to PublicationsSelf-interactive learning: Fusion and evolution of multi-scale histomorphology features for molecular traits prediction in computational pathology.
Journal article
Hu Y. et al, (2025), Medical image analysis, 101
Quantitative analysis of bone marrow fibrosis highlights heterogeneity in myelofibrosis and augments histological assessment: An Insight from a phase II clinical study of zinpentraxin alfa.
Journal article
Ryou H. et al, (2024), HemaSphere, 8
Image-based consensus molecular subtyping in rectal cancer biopsies and response to neoadjuvant chemoradiotherapy.
Journal article
Lafarge MW. et al, (2024), NPJ precision oncology, 8
Cluster Triplet Loss for Unsupervised Domain Adaptation on Histology Images
Conference paper
Wood R. et al, (2024), IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 5122 - 5131
Quantitative Analysis of Bone Marrow Features Highlights Heterogeneity in Myelofibrosis Patients Treated with Zinpentraxin Alfa in a Phase II Clinical Study
Journal article
Ryou H. et al, (2023), BLOOD, 142
Enhancing Local Context of Histology Features in Vision Transformers
Conference paper
Wood R. et al, (2022)
Predicting Molecular Traits from Tissue Morphology Through Self-interactive Multi-instance Learning
Conference paper
Hu Y. et al, (2022), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13432 LNCS, 130 - 139