Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Wysocki Oskar"'
Syllogistic reasoning is crucial for Natural Language Inference (NLI). This capability is particularly significant in specialized domains such as biomedicine, where it can support automatic evidence interpretation and scientific discovery. This paper
Externí odkaz:
http://arxiv.org/abs/2410.14399
Autor:
Wysocki, Oskar, Wysocka, Magdalena, Carvalho, Danilo, Bogatu, Alex Teodor, Gusicuma, Danilo Miranda, Delmas, Maxime, Unsworth, Harriet, Freitas, Andre
We present BioLunar, developed using the Lunar framework, as a tool for supporting biological analyses, with a particular emphasis on molecular-level evidence enrichment for biomarker discovery in oncology. The platform integrates Large Language Mode
Externí odkaz:
http://arxiv.org/abs/2406.18626
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 domain experts. Inferring over and extracting information from Large Lang
Externí odkaz:
http://arxiv.org/abs/2305.17819
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, supporting the interpretation and analysis of complex discourse and d
Externí odkaz:
http://arxiv.org/abs/2303.03235
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
Publikováno v:
In Journal of Biomedical Informatics October 2024 158
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