[HTML][HTML] Artificial intelligence in emergency medicine: viewpoint of current applications and foreseeable opportunities and challenges
Emergency medicine and its services have reached a breaking point during the COVID-19
pandemic. This pandemic has highlighted the failures of a system that needs to be …
pandemic. This pandemic has highlighted the failures of a system that needs to be …
Improved Mask-CTC for non-autoregressive end-to-end ASR
For real-world deployment of automatic speech recognition (ASR), the system is desired to
be capable of fast inference while relieving the requirement of computational resources. The …
be capable of fast inference while relieving the requirement of computational resources. The …
Context-aware adversarial training for name regularity bias in named entity recognition
In this work, we examine the ability of NER models to use contextual information when
predicting the type of an ambiguous entity. We introduce NRB, a new testbed carefully …
predicting the type of an ambiguous entity. We introduce NRB, a new testbed carefully …
A retrospective study on machine learning-assisted stroke recognition for medical helpline calls
Advanced stroke treatment is time-dependent and, therefore, relies on recognition by call-
takers at prehospital telehealth services to ensure fast hospitalisation. This study aims to …
takers at prehospital telehealth services to ensure fast hospitalisation. This study aims to …
[HTML][HTML] Machine learning can support dispatchers to better and faster recognize out-of-hospital cardiac arrest during emergency calls: a retrospective study
F Byrsell, A Claesson, M Ringh, L Svensson… - Resuscitation, 2021 - Elsevier
Aim Fast recognition of out-of-hospital cardiac arrest (OHCA) by dispatchers might increase
survival. The aim of this observational study of emergency calls was to (1) examine whether …
survival. The aim of this observational study of emergency calls was to (1) examine whether …
Speaker conditioning of acoustic models using affine transformation for multi-speaker speech recognition
This study addresses the problem of single-channel Automatic Speech Recognition of a
target speaker within an overlap speech scenario. In the proposed method, the hidden …
target speaker within an overlap speech scenario. In the proposed method, the hidden …
On scaling contrastive representations for low-resource speech recognition
Recent advances in self-supervised learning through contrastive training have shown that it
is possible to learn a competitive speech recognition system with as little as 10 minutes of …
is possible to learn a competitive speech recognition system with as little as 10 minutes of …
Using natural language processing techniques to study and regulate emergency department flows: development and application to the study of trauma risks based on …
G Chenais - 2023 - theses.hal.science
The TARPON (Traitement Automatique des Résumés de Passage aux urgences dans le but
de créer un Observatoire National du traumatisme) project aims to demonstrate the …
de créer un Observatoire National du traumatisme) project aims to demonstrate the …
Speech-to-text models to transcribe emergency calls
JA Thuestad, Ø Grutle - 2023 - bora.uib.no
This thesis is part of the larger project “AI-Support in Medical Emergency Calls (AISMEC)”,
which aims to develop a decision support system for Emergency Medical Communication …
which aims to develop a decision support system for Emergency Medical Communication …