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ML-Based Early Warning System
ML-Based Early Warning System is responsible to provide the necessary notifications (warnings and/or alerts) to the end users in case of potential outbreaks taking into consideration certain rules and patterns based on Machine Learning models. Support users in order to identify needs on material resources, while assist authorities to monitor and validate the effectiveness of policies and measures that are applied.
BIMS_WN West Nile epidemics model.
The BIMS_WN model is a muti-agent model whose goal is to predict the occurrence of a WN epidemic using climate and bird migration and movement data.
COVID-19 Information and Symptom Checker chatbot
If people know the facts and check their symptoms, they can be guided on when it’s necessary to isolate themselves, visit health facilities, or continue to follow recommended practices to slow the spread of the disease.
InteleSafe
An app and website for health workers to learn how to stay safe while on the job.
CovidMonitoring
For employers and healthcare organizations to monitor employees, patients, and other individuals
GetWell Loop
Engage all patients across their care journey through automated virtual check-ins.
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Portfolio of Solutions web site has been initially developed in the scope of DRIVER+ project. Today, the service is managed by AIT Austrian Institute of Technology GmbH., for the benefit of the European Management. PoS is endorsed and supported by the Disaster Competence Network Austria (DCNA) as well as by the STAMINA and TeamAware H2020 projects. |