activity
20202023
most citedAssessing the communication gap between AI models and healthcare professionals: explainability, utility and trust in AI-driven clinical decision-making

153 citations · 175 across the 7 of their papers we have counts for

collaborators

7 papers

cs.HC2023★ 1 cited

On the Visualisation of Argumentation Graphs to Support Text Interpretation

Hanadi Mardah, Oskar Wysocki, Markel Vigo +1

The recent evolution in Natural Language Processing (NLP) methods, in particular in the field of argumentation mining, has the potential to transform the way we interact with text,…

q-bio.QM2022

A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data

Magdalena Wysocka, Oskar Wysocki, Marie Zufferey +2

There is an increasing interest in the use of Deep Learning (DL) based methods as a supporting analytical framework in oncology. However, most direct applications of DL will delive…

q-bio.QM2022

Metareview-informed Explainable Cytokine Storm Detection during CAR-T cell Therapy

Alex Bogatu, Magdalena Wysocka, Oskar Wysocki +4

Cytokine release syndrome (CRS), also known as cytokine storm, is one of the most consequential adverse effects of chimeric antigen receptor therapies that have shown promising res…

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.CL2021

Architectures of Meaning, A Systematic Corpus Analysis of NLP Systems

Oskar Wysocki, Malina Florea, Donal Landers +1

This paper proposes a novel statistical corpus analysis framework targeted towards the interpretation of Natural Language Processing (NLP) architectural patterns at scale. The prop…

cs.CL2020★ 2 cited

What is SemEval evaluating? A Systematic Analysis of Evaluation Campaigns in NLP

Oskar Wysocki, Malina Florea, Andre Freitas

SemEval is the primary venue in the NLP community for the proposal of new challenges and for the systematic empirical evaluation of NLP systems. This paper provides a systematic qu…