Research graph
References from Hierarchical vision transformers for Epstein-Barr virus status and histological subtype prediction in Hodgkin lymphoma whole-slide images. Local targets link to admitted publications; unresolved targets remain external evidence.
Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
2024 · External reference
Incidence, mortality, risk factors, and trends for Hodgkin lymphoma: a global data analysis
10.1186/s13045-022-01281-9 · 2022 · External reference
Classical Hodgkin lymphoma
10.1016/s0140-6736(20)32207-8 · 2021 · External reference
Unresolved reference
2020 · External reference
Impact of treatment site on disparities in outcome among adolescent and young adults with Hodgkin lymphoma
10.1038/leu.2017.66 · 2017 · External reference
Hodgkin lymphoma: late effects of treatment and guidelines for surveillance
10.1053/j.seminhematol.2016.05.008 · 2016 · External reference
Global patterns of Hodgkin lymphoma incidence and mortality in 2020 and a prediction of the future burden in 2040
10.1002/ijc.33948 · 2022 · External reference
Epidemiology of Hodgkin’s disease
1966 · External reference
An update on the pathology and molecular features of Hodgkin lymphoma
10.3390/cancers14112647 · 2022 · External reference
Hodgkin lymphoma
10.1038/s41572-020-0189-6 · 2020 · External reference
The 5th edition of the world health organization classification of mature lymphoid and stromal tumours – an overview and update
10.1080/10428194.2023.2297939 · 2024 · External reference
Unresolved reference
2017 · External reference
Epstein–barr virus-associated Hodgkin’s lymphoma
10.1111/j.1365-2141.2004.04902.x · 2004 · External reference
An etiological role for the Epstein-Barr virus in the pathogenesis of classical Hodgkin lymphoma
10.1182/blood.2019000568 · 2019 · External reference
Prevalence and prognostic significance of Epstein-Barr virus infection in classical Hodgkin’s lymphoma: a meta-analysis
10.1016/j.arcmed.2014.06.001 · 2014 · External reference
Frequency of EBV associated classical Hodgkin lymphoma decreases over a 54-year period in a Brazilian population
10.1038/s41598-018-20133-6 · 2018 · External reference
Are EBV-related and EBV-unrelated Hodgkin lymphomas different with regard to susceptibility to checkpoint blockade?
10.1182/blood-2018-02-833806 · 2018 · External reference
Epstein-Barr virus-associated Hodgkin’s disease: epidemiologic characteristics in international data
10.1002/(sici)1097-0215(19970207)70:4<375::aid-ijc1>3.0.co;2-t · 1997 · External reference
Cigarette smoking and risk of Hodgkin lymphoma and its subtypes: a pooled analysis from the International Lymphoma Epidemiology Consortium (InterLymph)
10.1093/annonc/mdt218 · 2013 · External reference
Epstein Barr virus-associated Hodgkin lymphoma
10.3390/cancers10060163 · 2018 · External reference
The circuitry of the tumour microenvironment in adult and pediatric Hodgkin lymphoma: cellular composition, cytokine profile, EBV, and exosomes
2021 · External reference
The microenvironment of classical Hodgkin lymphoma: heterogeneity by Epstein-Barr virus presence and location within the tumour
10.1038/bcj.2016.26 · 2016 · External reference
Hodgkin lymphoma classification-from historical concepts to current refinements
10.3390/cancers17172929 · 2025 · External reference
Molecular biology of Hodgkin lymphoma
10.1038/s41375-021-01204-6 · 2021 · External reference
Autoimmune and atopic disorders and risk of classical Hodgkin lymphoma
10.1093/aje/kwv081 · 2015 · External reference
Artificial intelligence in lymphoma histopathology: systematic review
10.2196/62851 · 2025 · External reference
Enhancing lymphoma cancer detection using deep transfer learning on histopathological images
10.1038/s41598-025-21888-5 · 2025 · External reference
Autoencoder-assisted stacked ensemble learning for lymphoma subtype classification: a hybrid deep learning and machine learning approach
2025 · External reference
Automatic classification of lymphoma images with transform-based global features
10.1109/titb.2010.2050695 · 2010 · External reference
LymphoML: an interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype
2023 · External reference
Bioinformatics analysis of whole slide images reveals significant neighborhood preferences of tumour cells in Hodgkin lymphoma
10.1371/journal.pcbi.1007516 · 2020 · External reference
An artificial intelligence method using FDG PET to predict treatment outcome in diffuse large B cell lymphoma patients
10.1038/s41598-023-40218-1 · 2023 · External reference
Diffuse large B-cell lymphoma in the new era: prognostic tools for mapping risk
10.1007/s00277-025-06686-3 · 2025 · External reference
A novel hybrid convolutional and transformer network for lymphoma classification
10.1038/s41598-025-11277-3 · 2025 · External reference
A vision transformer-based framework for knowledge transfer from multi-modal to mono-modal lymphoma subtyping models
10.1109/jbhi.2024.3407878 · 2024 · External reference
Time trends in Hodgkin’s disease incidence. The role of diagnostic accuracy
10.1002/1097-0142(19901115)66:10<2196::aid-cncr2820661026>3.0.co;2-r · 1990 · External reference
The Scotland and Newcastle epidemiological study of Hodgkin’s disease: impact of histopathological review and EBV status on incidence estimates
10.1136/jcp.56.11.811 · 2003 · External reference
Inter- and intra-observer reliability of Epstein-Barr virus detection in Hodgkin lymphoma using histochemical procedures
10.1080/1042819032000141310 · 2004 · External reference
Scaling vision transformers to gigapixel images via hierarchical self-supervised learning
2022 · External reference
Epidemiological evidence for the role of puberty and immune senescence in Hodgkin lymphoma aetiology from 1992 Danish cases
10.1002/ijc.70305 · 2026 · External reference
Attention-based deep multiple instance learning
2018 · External reference
Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
10.1038/s41591-019-0508-1 · 2019 · External reference
Data-efficient and weakly supervised computational pathology on whole-slide images
10.1038/s41551-020-00682-w · 2021 · External reference
Benchmarking embedding aggregation methods in computational pathology: a clinical data perspective
2024 · External reference
A fast and refined cancer regions segmentation framework in whole-slide breast pathological images
10.1038/s41598-018-37492-9 · 2019 · External reference
HistoSegNet: semantic segmentation of histological tissue type in whole slide images
2019 · External reference
Unresolved reference
2024 · External reference
Towards a general-purpose foundation model for computational pathology
10.1038/s41591-024-02857-3 · 2024 · External reference
Emerging properties in self-supervised vision transformers
2021 · External reference
Unresolved reference
2019 · External reference
Optuna: a next-generation hyperparameter optimization framework
2019 · External reference
Deep learning for whole slide image analysis: an overview
10.3389/fmed.2019.00264 · 2019 · External reference
Digital transformation of pathology - the European Society of Pathology expert opinion paper
10.1007/s00428-025-04090-w · 2025 · External reference
Stain normalization in digital pathology: clinical multi-center evaluation of image quality
10.1016/j.jpi.2022.100145 · 2022 · External reference
Clinical significance of aetiological heterogeneity in classical Hodgkin lymphoma
10.20517/jtgg.2021.46 · 2022 · External reference
Distinct Hodgkin lymphoma subtypes defined by noninvasive genomic profiling
10.1038/s41586-023-06903-x · 2024 · External reference
Circulating tumour DNA sequencing for biologic classification and individualized risk stratification in patients with Hodgkin lymphoma
10.1200/jco.23.01867 · 2024 · External reference
