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CBR assisted context-aware surface realisation for data-to-text generation. (2023)
Presentation / Conference
UPADHYAY, A. and MASSIE, S. 2023. CBR assisted context-aware surface realisation for data-to-text generation. In Proceedings of the 31st International conference on case-based reasoning 2023 (ICCBR-2023): CBR in a data-driven world, 17-20 July 2023, Aberdeen, UK. Aberdeen: ICCBR [online], paper 28. Available from: https://delegate.iccbr2023.org/res/paper_28.pdf

Current state-of-the-art neural systems for Data-to-Text Generation (D2T) struggle to generate content from past events with interesting insights. This is because these systems have limited access to historic data and can also hallucinate inaccurate... Read More about CBR assisted context-aware surface realisation for data-to-text generation..

Machine learning for risk stratification of diabetic foot ulcers using biomarkers. (2023)
Conference Proceeding
MARTIN, K., UPHADYAY, A., WIJEKOON, A., WIRATUNGA, N. and MASSIE, S. [2023]. Machine learning for risk stratification of diabetic foot ulcers using biomarkers. To be presented at the 2023 International conference on computational science (ICCS 2023): computing at the cutting edge of science, 3-5 July 2023, Prague, Czech Republic: [virtual event].

Development of a Diabetic Foot Ulcer (DFU) causes a sharp decline in a patient's health and quality of life. The process of risk stratification is crucial for informing the care that a patient should receive to help manage their Diabetes before an ul... Read More about Machine learning for risk stratification of diabetic foot ulcers using biomarkers..