Novel machine learning techniques to improve the forecasting of stroke post-interventive outcomes

Project Information

MAESTRO

Grant agreement ID: 101027770

DOI

10.3030/101027770

Project terminated on 16 July 2023

EC signature date 23 April 2021

Start date 1 March 2022

End date 28 February 2025

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 245 732,16

EU contribution

€ 245 732,16

Coordinated by

FUNDACION IMDEA NETWORKS
Spain

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Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Conference proceedings (1)

When BERT Fails -- The Limits of EHR Classification

Author(s): Augusto Garcia-Agundez Carsten Eickhoff
Published in: American Medical Informatics Association 2022 Annual Symposium / Arxiv, Issue Yearly, 2022
Publisher: Arxiv
DOI: 10.48550/arxiv.2208.10245

Peer reviewed articles (1)

Delirium detection using wearable sensors and machine learning in patients with intracerebral hemorrhage

Author(s): Abdullah Ahmed1† Augusto Garcia-Agundez1,2† Ivana Petrovic1 Fatemeh Radaei1 James Fife1 John Zhou1 Hunter Karas1 Scott Moody3 Jonathan Drake3 Richard N. Jones4 Carsten Eickhoff1*‡ Michael E. Reznik3*‡
Published in: Frontiers in Neurology, 2023, ISSN 1664-2295
Publisher: Frontiers Research Foundation
DOI: 10.3389/fneur.2023.1135472

Other (1)

AI-Driven Stroke Post-Rehabilitation Outcome Prediction: A Systematic Review of the Evidence

Author(s): Augusto Garcia Agundez, Antonio Fernandez Anta, Michael E Reznik, Carsten Eickhoff
Published in: 2023
Publisher: Manuscript in Preparation