1k citations
- University of CambridgeGB6 papers
- AstraZeneca (Sweden)SE4 papers
- Medical University of ViennaAT4 papers
- University of ManchesterGB4 papers
- Addenbrooke's HospitalGB3 papers
- Cambridge University Hospitals NHS Foundation TrustGB3 papers
- Genomics (United Kingdom)GB3 papers
- Imperial College LondonGB3 papers
- Mila - Quebec Artificial Intelligence InstituteCA3 papers
- Novartis (Switzerland)CH3 papers
- Roche (Switzerland)CH3 papers
- University College LondonGB3 papers
26 papers
Publishing Neural Networks in Drug Discovery Might Compromise Training Data Privacy
Fabian P. Krüger, Johan Östman, Lewis Mervin +2
This study investigates the risks of exposing confidential chemical structures when machine learning models trained on these structures are made publicly available. We use membersh…
The Role of Graph Topology in the Performance of Biomedical Knowledge Graph Completion Models
Alberto Cattaneo, Stephen Bonner, Thomas Martynec +4
Knowledge Graph Completion has been increasingly adopted as a useful method for helping address several tasks in biomedical research, such as drug repurposing or drug-target identi…
The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems
Jakob Mokander, Margi Sheth, David Watson +1
Organisations that design and deploy artificial intelligence (AI) systems increasingly commit themselves to high-level, ethical principles. However, there still exists a gap betwee…
Challenges and Best Practices in Corporate AI Governance:Lessons from the Biopharmaceutical Industry
Jakob Mökander, Margi Sheth, Mimmi Gersbro-Sundler +2
While the use of artificial intelligence (AI) systems promises to bring significant economic and social benefits, it is also coupled with ethical, legal, and technical challenges.…
Potential outcome simulation for efficient head-to-head comparison of adaptive dose-finding designs
Michael Sweeting, Daniel Slade, Dan Jackson +1
Dose-finding trials are a key component of the drug development process and rely on a statistical design to help inform dosing decisions. Triallists wishing to choose a design requ…
An end-to-end attention-based approach for learning on graphs
David Buterez, Jon Paul Janet, Dino Oglic +1
There has been a recent surge in transformer-based architectures for learning on graphs, mainly motivated by attention as an effective learning mechanism and the desire to supersed…