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6 papers · 1 filter
Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs
Stephen Bonner, Ufuk Kirik, Ola Engkvist +2
Adoption of recently developed methods from machine learning has given rise to creation of drug-discovery knowledge graphs (KG) that utilize the interconnected nature of the domain…
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence
Xiang Bai, Hanchen Wang, Liya Ma +43
Artificial intelligence (AI) provides a promising substitution for streamlining COVID-19 diagnoses. However, concerns surrounding security and trustworthiness impede the collection…
Quantifying sources of uncertainty in drug discovery predictions with probabilistic models
Stanley E. Lazic, Dominic P. Williams
Knowing the uncertainty in a prediction is critical when making expensive investment decisions and when patient safety is paramount, but machine learning (ML) models in drug discov…
Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery
Stephen Bonner, Ian P Barrett, Cheng Ye +4
Knowledge Graphs (KG) and associated Knowledge Graph Embedding (KGE) models have recently begun to be explored in the context of drug discovery and have the potential to assist in…
Sequence tagging for biomedical extractive question answering
Wonjin Yoon, Richard Jackson, Aron Lagerberg +1
Current studies in extractive question answering (EQA) have modeled the single-span extraction setting, where a single answer span is a label to predict for a given question-passag…
A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective
Stephen Bonner, Ian P Barrett, Cheng Ye +5
Drug discovery and development is a complex and costly process. Machine learning approaches are being investigated to help improve the effectiveness and speed of multiple stages of…