11 citations · 26 across the 6 of their papers we have counts for
6 papers
Consultation Checklists: Standardising the Human Evaluation of Medical Note Generation
Aleksandar Savkov, Francesco Moramarco, Alex Papadopoulos Korfiatis +3
Evaluating automatically generated text is generally hard due to the inherently subjective nature of many aspects of the output quality. This difficulty is compounded in automatic…
User-Driven Research of Medical Note Generation Software
Tom Knoll, Francesco Moramarco, Alex Papadopoulos Korfiatis +7
A growing body of work uses Natural Language Processing (NLP) methods to automatically generate medical notes from audio recordings of doctor-patient consultations. However, there…
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…
PriMock57: A Dataset Of Primary Care Mock Consultations
Alex Papadopoulos Korfiatis, Francesco Moramarco, Radmila Sarac +1
Recent advances in Automatic Speech Recognition (ASR) have made it possible to reliably produce automatic transcripts of clinician-patient conversations. However, access to clinica…
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…
A preliminary study on evaluating Consultation Notes with Post-Editing
Francesco Moramarco, Alex Papadopoulos Korfiatis, Aleksandar Savkov +1
Automatic summarisation has the potential to aid physicians in streamlining clerical tasks such as note taking. But it is notoriously difficult to evaluate these systems and demons…