All Outputs (3)

Explainable text-tabular models for predicting mortality risk in companion animals (2024)
Journal Article
Burton, J., Farrell, S., Mäntylä Noble, P.-J., & Al Moubayed, N. (2024). Explainable text-tabular models for predicting mortality risk in companion animals. Scientific Reports, 14(1), Article 14217. https://doi.org/10.1038/s41598-024-64551-1

As interest in using machine learning models to support clinical decision-making increases, explainability is an unequivocal priority for clinicians, researchers and regulators to comprehend and trust their results. With many clinical datasets contai... Read More about Explainable text-tabular models for predicting mortality risk in companion animals.

Natural Language Explanations for Machine Learning Classification Decisions (2023)
Presentation / Conference Contribution
Burton, J., Al Moubayed, N., & Enshaei, A. (2023, June). Natural Language Explanations for Machine Learning Classification Decisions. Presented at 2023 International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia

This paper addresses the challenge of providing understandable explanations for machine learning classification decisions. To do this, we introduce a dataset of expert-written textual explanations paired with numerical explanations, forming a data-to... Read More about Natural Language Explanations for Machine Learning Classification Decisions.

Generating Textual Explanations for Machine Learning Models Performance: A Table-to-Text Task (2022)
Presentation / Conference Contribution
Ampomah, I., Burton, J., Enshaei, A., & Al Moubayed, N. (2022, June). Generating Textual Explanations for Machine Learning Models Performance: A Table-to-Text Task. Presented at 13th Conference on Language Resources and Evaluation (LREC 2022), Marseille, France

Numerical tables are widely employed to communicate or report the classification performance of machine learning (ML) models with respect to a set of evaluation metrics. For non-experts, domain knowledge is required to fully understand and interpret... Read More about Generating Textual Explanations for Machine Learning Models Performance: A Table-to-Text Task.