Artificial Intelligence for Emergency Medical Services: a smart digital assistant for faster and more accurate cardiac arrest recognition during emergency calls

Informations projet

AI4EMS

N° de convention de subvention: 823383

DOI 10.3030/823383

Projet clôturé

Date de signature de la CE 20 Août 2018

Date de début 1 Août 2018

Date de fin 31 Janvier 2020

Financé au titre de

• INDUSTRIAL LEADERSHIP - Innovation In SMEs

Coût total € 2 055 976,25

Contribution de l’UE € 1 439 183,00

Coordonné par

CORTI APS
Denmark

Livrables

Websites, patent fillings, videos etc. (1)

AI4EMS online content

AI4EMS online content. The project content will be divide in a public section and a restricted area (accessible only to the project participants and the EC officers allocated to the project) for uploading and downloading of all of the project reports and documents.

Publications

Peer reviewed articles (1)

Machine learning as a supportive tool to recognize cardiac arrest in emergency calls

Auteurs: Stig Nikolaj Blomberg, Fredrik Folke, Annette Kjær Ersbøll, Helle Collatz Christensen, Christian Torp-Pedersen, Michael R. Sayre, Catherine R. Counts, Freddy K. Lippert
Publié dans: Resuscitation, Numéro 138, 2019, Page(s) 322-329, ISSN 0300-9572
Éditeur: Elsevier BV
DOI: 10.1016/j.resuscitation.2019.01.015

Conference proceedings (5)

Utilizing Domain Knowledge in End-to-End Audio Processing

Auteurs: Tycho Max Sylvester Tax, Jose Luis Diez Antich, Hendrik Purwins, Lars Maaløe
Publié dans: 31st Conference on Neural Information Processing Systems (NIPS 2017), 2017
Éditeur: NIPS

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling

Auteurs: Lars Maaløe, Marco Fraccaro, Valentin Liévin, Ole Winther
Publié dans: arXiv preprint arXiv:1902.02102, 2019
Éditeur: arXiv

Exploiting Nontrivial Connectivity for Automatic Speech Recognition

Auteurs: Marius Paraschiv, Lasse Borgholt, Tycho Max Sylvester Tax, Marco Singh, Lars Maaløe
Publié dans: NIPS workshop on machine learning for audio, 2017
Éditeur: NIPS

On the Inductive Bias of Word-Character-Level Multi-Task Learning for Speech Recognition

Auteurs: Jan Kremer, Corti, Copenhagen, Denmark, [e-mail] Lasse Borgholt, Corti, Copenhagen, Denmark, [e-mail] Lars Maaløe , Corti, Copenhagen, Denmark, [e-mail]
Publié dans: 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), 2018
Éditeur: NIPS

Towards Hierarchical Discrete Variational Autoencoders

Auteurs: Valentin Liévin, Andrea Dittadi, Lars Maaløe, Ole Winther
Publié dans: NeurIPS Workshop on Advances in Approximate Bayesian Inference, 2019
Éditeur: OpenReview

Other (1)

Detecting Out-of-Hospital Cardiac Arrest Using Artificial Intelligence

Auteurs: Andreas Cleve, Dimitri Devillers, Matteo Palladini, Jerome Paris, Rose Michael, Etienne Faure, Rodolfo Bonora
Publié dans: 2020
Éditeur: European Emergency Number Association