24 citations · 38 across the 3 of their papers we have counts for
3 papers
Human Evaluation and Correlation with Automatic Metrics in Consultation Note Generation
Francesco Moramarco, Alex Papadopoulos Korfiatis, Mark Perera +5
In recent years, machine learning models have rapidly become better at generating clinical consultation notes; yet, there is little work on how to properly evaluate the generated c…
Towards more patient friendly clinical notes through language models and ontologies
Francesco Moramarco, Damir Juric, Aleksandar Savkov +8
Clinical notes are an efficient way to record patient information but are notoriously hard to decipher for non-experts. Automatically simplifying medical text can empower patients…
Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word Vectors
Vitalii Zhelezniak, Aleksandar Savkov, April Shen +3
Recent literature suggests that averaged word vectors followed by simple post-processing outperform many deep learning methods on semantic textual similarity tasks. Furthermore, wh…