Speaker: Abir Elbeji (Department of Precision Health, Luxembourg Institute of Health)
Title: Exploring Voice AI: Technologies, Algorithms, and Applications in Healthcare.
Time: Wednesday, 2024.05.15, 10:00 a.m. (CET)
Place: fully virtual (contact Jakub Lengiewicz or Elisa GÓMEZ DE LOPE to register)
Abstract: This presentation looks at Voice AI technology, one of the key players in artificial intelligence that’s making a major impact, especially in digital health. We’ll cover the basics of Voice AI, including the latest technologies and algorithms, and how they’re used in various industries, with a focus on healthcare. One exciting development is the use of vocal biomarkers in clinical settings, which are non-invasive ways to monitor and diagnose health conditions through voice analysis. We’ll discuss how combining voice technologies with advanced analysis can improve patient care, and lead to personalized medicine.
www.colivevoice.org
Abir Elbéji, third-year PhD student at the Luxembourg Institute of Health. My research focuses on investigating voice biomarkers for monitoring chronic disease symptoms using artificial intelligence (AI) technologies. Throughout my academic journey, I have engaged in innovative projects such as identifying a vocal biomarker for fatigue monitoring in COVID-19 patients, detecting type 2 diabetes using voice analysis, and examining vocal biomarkers for mental health, specifically depressive symptoms.
The aim of the Machine Learning Seminar series is to host presentations on fundamental and methodological advances in data science and machine learning, as well as to discuss application areas presented by domain specialists. The uniqueness of the seminar series lies in its attempt to extract common denominators between domain areas and to challenge existing methodologies. Therefore, the focus is on theory and applications to a wide range of domains, including Computational Physics and Engineering, Computational Biology and Life Sciences, and Computational Behavioural and Social Sciences. The seminar aims to bring together young and experienced researchers from various disciplines to exchange ideas on Machine Learning techniques. It is currently affiliated with the University of Luxembourg and is run under the auspices of the DTU DRIVEN PRIDE project, funded by the FNR, and the widening participation DRIVEN project, funded by H2020. The seminar also welcomes talks by researchers from a wider collaborative network, including but not limited to early-stage researchers in RAINBOW ITN, as well as current and incoming individual Marie Skłodowska-Curie fellows.
The usual format is as follows: a short presentation (20-30 minutes) followed by a longer discussion (30-40 minutes). The usual time is Wednesdays at 10:00 a.m. (CET). If you are interested in joining, please contact Jakub Lengiewicz. See www.jlengineer.eu/ml-seminar/.
28 май 2024
