8 projects

Covid-19 Detection by Cough and Voice Analysis (CDCVA)

Emergency service hospital center receives a huge number of calls in epidemic period, among these calls there are critical cases that need rapid intervention, it may be delayed to answer these cases. Therefore, we suggest a solution by giving an indication of health status of the person calling directly when hearing his voice and cough. This indicator depends on finding a degree of correspondence between the caller's voice, cough signatures and that of certain patients with the Covid-19 virus. The solution proposed by CDCVA project can also be used effectively by health professionals for re...

COVoiceID - Identification of COVID-19 from Voice

COVoiceID project proposes a machine learning based system that will use patient's voice and cough to detect repeating patterns, with the aim to discriminate between voices of healthy individuals and COVID-19 patients. COVID-19 is a respiratory condition, affecting breathing and voice, and causing, among other symptoms, dry cough, sore throat, excessively breathy voice and typical breathing patterns. These are all conditions that can make patients' voice distinctive, creating recognizable voice signatures. The ability to successfully identify COVID-19 patients from their voice will heavily...

INFODEMIC - Combating the Infodemic to Curb the Pandemic: A Step Towards a Reliable and Knowledg...

Building on SnT/Uni.lu expertise on text analytics and machine learning, we propose the INFODEMIC project to challenge fake news on social media. Our approach considers a holistic view in combating fake news. To that end, we develop three key work packages: (1) Archiving of viral fake news, where a wikipedia-like crowdsourcing approach is investigated for building a large and publicly-searchable repository of fake news; (2) Automating early detection of fake news, where transfer learning-based models are devised to flag potential fake news in a multilingual setting; (3) Integrating a relia...

Pandemic Simulation and Forecasting for an Empowered Policy-Making: Convergence of Machine Learni...

The COVID-19 pandemic has created a public health emergency unprecedented in this century. The lack of accurate knowledge regarding the outcomes of the virus has made it challenging for policymakers to decide on appropriate countermeasures to mitigate its impact on society, in particular the public health and the very healthcare system. Therefore, the PILOT project will support policymakers with simulation and forecasting tools of the pandemic. Similar tools have already been designed, as part of a collaborative endeavour of the Research Luxembourg taskforce, to assess the short-term imp...

Machine Learning to the Rescue: From Health Recovery to Economic Revival

REBORN is a data science project that focuses on the challenge of ensuring sustainable economic recovery in face of Covid-19. The project team will apply advanced Machine Learning and simulation techniques to yield recommendations of economic actions given different scenarios in which the lockdown is relaxed, partially or totally lifted. By interacting with other teams of the Luxembourg Task Force, this project targets high impact for the various sectors of the Luxembourg economy, through providing appropriate data-driven recommendations for political decision-makers. We expect that REBORN ...

Privacy Preserving Covid-19 Data Analytics Platform

The COVID-19 pandemic comes with an urgent need of exchanging confidential patient information among local and regional health organizations. Sharing knowledge is crucial for disease surveillance, protecting public health, fighting misinformation and managing the virus outbreak. Medical service providers are required to disclose facts about admissions, transfers and discharges to various entities like the patient's primary care practitioner and post-acute-care services providers. The dissemination of patients' medical records is subject to malicious activities. Most of the current sol...

Real-time Social Distancing Analysis

The idea of this project is to analyse if the Social Distancing measures decided by the government are being respected by the general population. To do so we propose to analyse anonymised video data in the City of Luxembourg.

MC19: Early Detection of Epidemics and Health Status Prediction Using Intelligent Wireless Body Sensors

MyelinS, a Luxembourgish startup (LLC in the incorporation phase) is proposing a novel solution for early detection of epidemics (particularly Covid-19), health status daily analysis, and prediction of critical health situations caused by the virus without any direct medical intervention, avoiding thereby any risk of transmission of the virus to the healthcare workers, as well as to healthy people. Unlike any existing solutions, the proposed detection and prediction system is non-invasive (on mobile phones), accurate, and rapid (detection in less than 1.5 minutes). The proposed solution ...

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