most citedAssessing the communication gap between AI models and healthcare professionals: explainability, utility and trust in AI-driven clinical decision-making

153 citations

5 papers

cs.CL2023★ 18 cited

Large Language Models, scientific knowledge and factuality: A framework to streamline human expert evaluation

Magdalena Wysocka, Oskar Wysocki, Maxime Delmas +2

The paper introduces a framework for the evaluation of the encoding of factual scientific knowledge, designed to streamline the manual evaluation process typically conducted by dom…

cs.AI2022★ 153 cited

Assessing the communication gap between AI models and healthcare professionals: explainability, utility and trust in AI-driven clinical decision-making

Oskar Wysocki, Jessica Katharine Davies, Markel Vigo +4

This paper contributes with a pragmatic evaluation framework for explainable Machine Learning (ML) models for clinical decision support. The study revealed a more nuanced role for…

cs.CL2022★ 19 cited

Transformers and the representation of biomedical background knowledge

Oskar Wysocki, Zili Zhou, Paul O'Regan +4

Specialised transformers-based models (such as BioBERT and BioMegatron) are adapted for the biomedical domain based on publicly available biomedical corpora. As such, they have the…

cs.LG2022★ 8 cited

A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples

Natalia Garcia Martin, Stefano Malacrino, Marta Wojciechowska +8

Multiplexed immunofluorescence provides an unprecedented opportunity for studying specific cell-to-cell and cell microenvironment interactions. We employ graph neural networks to c…

q-bio.OT2022★ 77 cited

A new Standard DNA damage (SDD) data format

J. Schuemann, A. McNamara, J. W. Warmenhoven +48

Our understanding of radiation induced cellular damage has greatly improved over the past decades. Despite this progress, there are still many obstacles to fully understanding how…