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The BRAINTEASER project, bringing Artificial Intelligence home for a better care of amyotrophic lateral sclerosis and multiple sclerosis, kicks off today!

Officially started on the 1st January 2021, the H2020 BRAINTEASER project launches today its operational activities. The project’s kick off meeting, organised in two days January 28thand 29th 2021, will gather together the project’s partners, a multidisciplinary gender-balanced consortium from academia, industry, clinical settings and the non-profit sector, active in six European Countries.

The BRAINTEASER project, that involves 11 partners and is led by the Universidad Politécnica de Madrid, will face the ambitious challenge of using Artificial Intelligence (AI) systems to process data gathered from patients affected by Multiple Sclerosis (MS) and Amyotrophic Lateral Sclerosis (ALS) to make patients’ management more efficient and effective and to develop models able to predict the disease progression.

READ THE EVERYTHING @ EU INSIDER:

The BRAINTEASER project, bringing Artificial Intelligence home for a better care of amyotrophic lateral sclerosis and multiple sclerosis, kicked off!

BRAINTEASER has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No GA 101017598

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Invited Talk @ ESCI-2019 – Session Bioinformatics and Machine Learning in Biomedicine

Invited talk “Predicting disease progression in Amyotrophic Lateral Sclerosis using Machine Learning: Learning from longitudinal data using time windows and progression patterns”, 53rd Annual Scientific Meeting of the ESCI (European Society for Clinical Investigation) – ESCI-2019,  Session Bioinformatics and Machine Learning in Biomedicine, 22nd May, Coimbra, Portugal.

Project manager of Lisbon Urban Data Laboratory @ FCUL

LxDataLab is a project resulting from a partnership between the Municipality of Lisbon and several higher education and research establishments. Its mission is to create analytics and data visualization solutions supported in Big Data, able to improve planning and operation and emergency management in the city of Lisbon, contributing to the sustainable improvement of resilience and quality of life of those who live or work in Lisbon, or just visit the city.

 

Paper accepted at IEEE ICDM DMBIH 2018: DMBIH’18 – The Sixth Workshop on Data Mining in Biomedical Informatics and Healthcare @ IEEE International Conference on Data Mining 2018

Sofia Pires, Marta Gromicho, Susana Pinto , Manuela Guerreiro, Mamede de Carvalho and Sara C. Madeira, “Predicting Non-Invasive Ventilation in ALS Patients using Stratified Disease Progression Groups”, accepted for publication at DMBIH’18 – The Sixth Workshop on Data Mining in Biomedical Informatics and Healthcare @ IEEE International Conference on Data Mining 2018.