Chris Harbron

Roche (United Kingdom) — United Kingdom

Biochemistry, Genetics and Molecular Biology · Life Sciences

23h-index2.2kcitations144works1.82yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Melanoma and MAPK Pathways(38), Computational Drug Discovery Methods(23), Protein Degradation and Inhibitors(20), Gene expression and cancer classification(18), Synthesis and biological activity(16)

Publications144 total

Prognostic pan-cancer and single-cancer models: A large-scale analysis using a real-world clinico-genomic database
PLoS ONE·2026Open Access
Meta-Analysis of Bias in Non–Small Cell Lung Cancer External Control Arms That Use Real-World Progression-Free Survival as the End Point
JCO Clinical Cancer Informatics·2025
Tying Together Loose Ends With uniLasso
Harvard Data Science Review·2025Open Access
The Challenge of Handling Structured Missingness in Integrated Data Sources
Advanced Intelligent Discovery·2025Open Access
Clinicians must participate in the development of multimodal AI
EClinicalMedicine·2025· 4 citedOpen Access
Personalized uncertainty quantification in artificial intelligence
Nature Machine Intelligence·2025· 13 citedOpen Access
Deep learning as Ricci flow
Scientific Reports·2024· 2 citedOpen Access
A multi‐arm multi‐stage platform design that allows preplanned addition of arms while still controlling the family‐wise error
Statistics in Medicine·2024Open Access
Deep Learning as Ricci Flow
Research Square (Research Square)·2024Open Access
Deep Learning as Ricci Flow
arXiv (Cornell University)·2024Open Access
Implementation of Statistical Innovation in a Pharmaceutical Company
Statistics in Biopharmaceutical Research·2024· 1 citedOpen Access
Prognostic pan-cancer and single-cancer models: A large-scale analysis using a real-world clinico-genomic database
2023Open Access
Minimal Residual Disease Status Predicts Outcome in Patients With Previously Untreated Follicular Lymphoma: A Prospective Analysis of the Phase III GALLIUM Study
Journal of Clinical Oncology·2023· 29 citedOpen Access
Clinical AI tools must convey predictive uncertainty for each individual patient
Nature Medicine·2023· 42 citedOpen Access
A Complete Characterisation of Structured Missingness
arXiv (Cornell University)·2023Open Access
Anonymising Clinical Data for Secondary Use
arXiv (Cornell University)·2023· 1 citedOpen Access
Learning from data with structured missingness
arXiv (Cornell University)·2023Open Access
Supplemental Table and Figure Legends from Reproducible, Quantitative, and Flexible Molecular Subtyping of Clinical DLBCL Samples Using the NanoString nCounter System
2023Open Access
Data from Reproducible, Quantitative, and Flexible Molecular Subtyping of Clinical DLBCL Samples Using the NanoString nCounter System
2023Open Access
Supplemental Figure 1 from Reproducible, Quantitative, and Flexible Molecular Subtyping of Clinical DLBCL Samples Using the NanoString nCounter System
2023Open Access
page 1 of 8Next →

Frequent Co-authors

Christiane Pott(6), Eva Hoster(6), Kirsten Mundt(6), Darren Hodgson(5), Tapabrata Chakraborti(5), Ben D. MacArthur(5), Ian Peers(4), Britta Kehden(4), Christopher R. S. Banerji(4), Chris Womack(4), Marie C. South(3), Simon Lea(3), Dave Singh(3), Ryan Copping(3), Fredrik Nyberg(3), Nathalie Danesi(3), Robert Marcus(3), Wolfgang Hiddemann(3), Laurie H. Sehn(3), David Belada(3)