Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Landers, Donal"'
Autor:
Jullien, Maël, Valentino, Marco, Frost, Hannah, O'Regan, Paul, Landers, Donal, Freitas, André
How can we interpret and retrieve medical evidence to support clinical decisions? Clinical trial reports (CTR) amassed over the years contain indispensable information for the development of personalized medicine. However, it is practically infeasibl
Externí odkaz:
http://arxiv.org/abs/2305.03598
Autor:
Jullien, Maël, Valentino, Marco, Frost, Hannah, O'Regan, Paul, Landers, Donal, Freitas, André
This paper describes the results of SemEval 2023 task 7 -- Multi-Evidence Natural Language Inference for Clinical Trial Data (NLI4CT) -- consisting of 2 tasks, a Natural Language Inference (NLI) task, and an evidence selection task on clinical trial
Externí odkaz:
http://arxiv.org/abs/2305.02993
Entailment trees have been proposed to simulate the human reasoning process of explanation generation in the context of open--domain textual question answering. However, in practice, manually constructing these explanation trees proves a laborious pr
Externí odkaz:
http://arxiv.org/abs/2208.01376
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 deliver models with limited transparency and explainability, which constrain
Externí odkaz:
http://arxiv.org/abs/2207.00812
Autor:
Bogatu, Alex, Wysocka, Magdalena, Wysocki, Oskar, Butterworth, Holly, Landers, Donal, Kilgour, Elaine, Freitas, Andre
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 results in cancer treatment. When emerging, CRS could be identified by th
Externí odkaz:
http://arxiv.org/abs/2206.10612
Autor:
Wysocki, Oskar, Davies, Jessica Katharine, Vigo, Markel, Armstrong, Anne Caroline, Landers, Dónal, Lee, Rebecca, Freitas, André
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 ML explanation models, when these are pragmatically embedded in the cl
Externí odkaz:
http://arxiv.org/abs/2204.05030
Autor:
Wysocki, Oskar, Zhou, Zili, O'Regan, Paul, Ferreira, Deborah, Wysocka, Magdalena, Landers, Dónal, Freitas, André
Publikováno v:
Computational Linguistics 2022
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 potential to encode large-scale biological knowledge. We investigate
Externí odkaz:
http://arxiv.org/abs/2202.02432
This paper proposes a novel statistical corpus analysis framework targeted towards the interpretation of Natural Language Processing (NLP) architectural patterns at scale. The proposed approach combines saturation-based lexicon construction, statisti
Externí odkaz:
http://arxiv.org/abs/2107.08124
This paper describes N-XKT (Neural encoding based on eXplanatory Knowledge Transfer), a novel method for the automatic transfer of explanatory knowledge through neural encoding mechanisms. We demonstrate that N-XKT is able to improve accuracy and gen
Externí odkaz:
http://arxiv.org/abs/2105.05737
Autor:
Bogatu, Alex, Wysocka, Magdalena, Wysocki, Oskar, Butterworth, Holly, Pillai, Manon, Allison, Jennifer, Landers, Dónal, Kilgour, Elaine, Thistlethwaite, Fiona, Freitas, André
Publikováno v:
In Journal of Biomedical Informatics June 2023 142
