Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Korfiatis, Alex Papadopoulos"'
Autor:
Savkov, Aleksandar, Moramarco, Francesco, Korfiatis, Alex Papadopoulos, Perera, Mark, Belz, Anya, Reiter, Ehud
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 consultation note generation by differing opinions between medical exp
Externí odkaz:
http://arxiv.org/abs/2211.09455
Autor:
Knoll, Tom, Moramarco, Francesco, Korfiatis, Alex Papadopoulos, Young, Rachel, Ruffini, Claudia, Perera, Mark, Perstl, Christian, Reiter, Ehud, Belz, Anya, Savkov, Aleksandar
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 are very few studies on how such systems could be used in clinical pra
Externí odkaz:
http://arxiv.org/abs/2205.02549
Autor:
Moramarco, Francesco, Korfiatis, Alex Papadopoulos, Perera, Mark, Juric, Damir, Flann, Jack, Reiter, Ehud, Belz, Anya, Savkov, Aleksandar
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 consultation notes to understand the impact they may have on both the c
Externí odkaz:
http://arxiv.org/abs/2204.00447
Recent advances in Automatic Speech Recognition (ASR) have made it possible to reliably produce automatic transcripts of clinician-patient conversations. However, access to clinical datasets is heavily restricted due to patient privacy, thus slowing
Externí odkaz:
http://arxiv.org/abs/2204.00333
Autor:
Moramarco, Francesco, Juric, Damir, Savkov, Aleksandar, Flann, Jack, Lehl, Maria, Boda, Kristian, Grafen, Tessa, Zhelezniak, Vitalii, Gohil, Sunir, Korfiatis, Alex Papadopoulos, Hammerla, Nils
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 with valuable information about their health, while saving clinicians
Externí odkaz:
http://arxiv.org/abs/2112.12672
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 demonstrate that they are safe to be used in a clinical setting. To circumve
Externí odkaz:
http://arxiv.org/abs/2104.04402
Autor:
Knoll, Tom, Moramarco, Francesco, Korfiatis, Alex Papadopoulos, Young, Rachel, Ruffini, Claudia, Perera, Mark, Perstl, Christian, Reiter, Ehud, Belz, Anya, Savkov, Aleksandar
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 are very few studies on how such systems could be used in clinical pra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______119::b57bcaeb9394a772d46a4f6640e185ad
https://doras.dcu.ie/28646/1/2022.naacl-main.29.pdf
https://doras.dcu.ie/28646/1/2022.naacl-main.29.pdf
Autor:
Moramarco F; Babylon Health, London, UK., Juric D; Babylon Health, London, UK., Savkov A; Babylon Health, London, UK., Flann J; Babylon Health, London, UK., Lehl M; Babylon Health, London, UK., Boda K; Babylon Health, London, UK., Grafen T; Babylon Health, London, UK., Zhelezniak V; Babylon Health, London, UK., Gohil S; Babylon Health, London, UK., Korfiatis AP; Babylon Health, London, UK., Hammerla N; Babylon Health, London, UK.
Publikováno v:
AMIA ... Annual Symposium proceedings. AMIA Symposium [AMIA Annu Symp Proc] 2022 Feb 21; Vol. 2021, pp. 881-890. Date of Electronic Publication: 2022 Feb 21 (Print Publication: 2021).
