GAME CHANGERS

AI-powered diagnostic decision support system screening patients for COVID-19 and assisting general practitioners to triage patients depending on their differential diagnoses
0,1% of all patient consultations are Covid-19 related, while millions were either afraid or unable to access needed care. Lives have been lost as a result.The project develops a digital triaging tool for general practices, which (1) screens reliably COVID-19 infected persons to reduce the risk of spreading the virus,(2) helps both COVID-19 and Non-COVID-19 patients to orient themselves whether self- or professional management is required, and (3)assists physicians to diagnose more accurately.

Challenge #1 Early detection

Lead SME
Symptoma GmbH - Austria

Healthcare partner
Claudiana - Provincial High School of Health - Italy

Covid Armour: Large Scale Covid Risk Assessment Tool
Immyounity is a health program blending AI/ML and Indian traditional Ayurvedic Science to improve the root cause behind poor digestive health - poor metabolism and regular organ inflammations. It uses AI/ML to understand the metabolic profile of the patients and give them a set of personalized diet and lifestyle interventions without medication for 5 weeks to improve their metabolism and reduce daily organ inflammations.

Challenge #1 Early detection

Lead SME
Softbrik - Estonia

Healthcare partner
AyurVaid - India

COVID-19 Preparedness Platform
Provides all necessary information to evaluate the risk for each location and population group based on the analysis of mobility patterns and occurrence of new variants. Combining both data in a single and scalable digital tool, it helps authorities to take early measures on the advance of new variants.

Challenge #1 Early detection

Lead SME
Kido Dynamics - Switzerland

Healthcare partner
University of Valencia - Spain

Statistical Estimation for Group Testing Network Across Nations
Group testing refers to sampling biological specimens from individual patients and pooling them into groups to reduce testing demand and resources in laboratories. However, there does not exist a standard methodology to determine the optimal number of individuals to be pooled together. SEGTNAN creates innovative AI software that enables individualized group testing at any laboratory. Implementation of group testing can reduce the economic testing burden by eightfold and increase capacity by 133%.

Challenge #2 Innovative Diagnostics

Lead SME
SYNAPTIC ApS - Denmark

Rapid and intelligent exclusion of COVID-19 using Gaston scholar (Self-Calibration of HOspital data for Learning Algorithms and clinical Rules)
Identifying COVID-19 patients in hospitals is challenging as symptoms vary and the incidence rate varies greatly in time and location. The decision support system “GASTON scholar” safely excludes COVID-19 in more than 75% of admitted hospital patients, independent of a PCR-result. Therefore GASTON scholar saves test capacity and speeds up the diagnostic process to 1 hour.

Challenge #2 Innovative Diagnostics

Lead SME
Medical Decision Support systems B.V. - Netherlands

Healthcare partner
Catharina Hospital - Netherlands

Laboratory Optimizer for Mass Testing
LOMT is software for COVID-19 mass testing - for diagnostics, screening, and epidemiological monitoring. It extends the standard processes of molecular testing for SARS-CoV-2 RNA with advanced data analytics and pool testing.
The product can be used both in robotized and manual laboratories in a hospital, point-of-care, or mobile laboratory allowing the testing of 15 times more people with the existing resources by reducing the number of assays and the cost and time of each test.

Challenge #2 Innovative Diagnostics

Lead SME
Jetware SRL - Italy

Data-Driven COVID-19 Patient Prognosis Using The Inflammatory Biomarker Supar To Guide Early Triaging And Treatment
Through a better prognosis, the solution directly addresses overburdened healthcare systems and lack of effective treatments for high-risk patients caused by the COVID-19 pandemic.

Challenge #3 Personalized Care

Lead SME
ViroGates A/S - Denmark

Healthcare partner
Hvidovre Hospital - Denmark

Covid@home
BeWell and its medical partner AZMM want to monitor COVID-19 patients in their home setting to investigate how they can be treated in the best way to lower (re)admission rate in hospitals. The obtained data and information about the home care monitoring will lead to a better understanding how to distribute the burden between the hospital care and the homecare. BeWell also wants to investigate how obtained data can be shared in a larger community with respect to all GDPR regulations.

Challenge #4 Remote Care

Lead SME
BeWell Innovations NV - Belgium

Healthcare partner
Maria Middelares General Hospital - Belgium

Management and Assessment of coviD for Chronic diseAse Patients
MADCAP targets cardiovascular disease patients diagnosed with COVID-19 aiming to support their remote care. The scalable solution gives remote support for COVID-19 risk management for prevention of infection, for managing remote treatments and for dealing with infection and post-infection cases. Gathering clinical and contextual patient data, it will support doctors to improve the care process.

Challenge #4 Remote Care

Lead SME
AVATR srl - Italy

Healthcare partner
University Hospital Mater Domini of Catanzaro - Italy

Personalized Care and Remote Support for Patients and Healthcare Workers at Covid-19 Risk
Healthentia Care4COVID helps Hospitals and other Healthcare Organizations to improve their COVID-19 resilience and response by managing Covid-19 related symptoms of patients and health workers from remote and providing targeted support and care guidelines to them.

Challenge #4 Remote Care

Lead SME
Innovation Sprint Sprl - Belgium

Healthcare partner
Agostino Gemelli IRCCS University Hospital Foundation - Italy

COVID@HOME
COVID@HOME is a remote care system for COVID-19 patients, with mild symptoms or asymptomatic, who remain at home and are monitored remotely by medical professionals. Collecting patient medical history and vital signs from patients, the solution is able to analyze biomarker results using novel published scoring algorithms and machine learning tools. It will assist physicians in their decision making regarding treatment or hospitalization.

Challenge #4 Remote Care

Lead SME
Business and Bytes Ltd. (B&B) - Greece

Healthcare partner
Private Medical Clinic on Vascular Research (Vascular Research SA) - Greece

Coach Assistant via Projected and Conversational Interface to support the fight against COVID-19 pandemic
CAPTAIN-X focuses on remote personalised care and monitoring for people diagnosed with COVID-19 in order to avoid visiting a hospital if it is not needed while getting a timely reaction to their needs and care. CAPTAIN-X care technologies include speech recognition, AI for patient monitoring and video projectors.

Challenge #4 Remote Care

Lead SME
CAPTAIN COACH P.C. - Greece

Remote Automatic Diagnosis and Follow-Up of COVID-19 for Chronic Skin Disease Patients
Targets chronic skin disease patients diagnosed with COVID-19 and patients with cutaneous manifestations of COVID-19, aiming to support their remote care.

Challenge #4 Remote Care

Main Technologies
IA, machine learning, and computer vision

Lead SME
AI LABS GROUP SL - Spain

Healthcare partner
Hospital Universitario Torrejón de Ardóz - Spain

COVID-19 Rehabilitation Guided Through Computer Vision
Offers a home based rehabilitation solution, which does not need the actual presence of a doctor or physical therapist. It enhances the treatment process of COVID-19 patients while helping to empty hospitals and rehabilitation clinics.

Challenge #4 Remote Care

Lead SME
TRAK HEALTH SOLUTIONS - Spain

Healthcare partner
Clínica Asunción - Spain

Telemonitoring & Track Immunity on Covid-19
Telemonitors the evolution of the degree of immunity conferred by the SARS-CoV-2 vaccine in the population and its evolution over time.

Main Technologies
Machine Learning and AI

Lead SME
Hope Care SA - Portugal

Healthcare partner
Centro Hospitalar Universitário Cova da Beira - Portugal

Remote Care, Monitoring and Support of 3 patient cohorts for Symptoms, QoL and Impact
A virtual interactive, and secure remote monitoring and care system of COVID19 patients. For COVID-19 patients to self-manage care. For healthcare professionals to keep patients away from the hospital and to improve their quality of life, both in “short” and “long” COVID-19 situations.

Challenge #4 Remote Care

Lead SME
Care Across Ltd. - UK

Intelligent Pervasive Monitoring of COVID-19 Patients using IoT and Cloud
Facilitates remote, automated and continuous monitoring, and coaching of patients suffering from COVID-19 symptoms and post-COVID syndrome.

Main Technologies
Internet of Medical Things, Microservices, AI and Data Analytics

Lead SME
BioAssist S.A. - Greece

Healthcare partner
The 1st Department of Critical Care Medicine and Pulmonary Services of the Medical School of National and Kapodistrian University of Athens at “Evangelismos” Hospital - Greece

Accurate Radiological Tracking for COVID-19 Induced Brain Harm
Based on a cloud-based computing platform for the post- processing of medical images of the brain, the solution provides secure access to a set of advanced image processing algorithms for quantification of brain abnormalities, allowing for both visual identification of clinical features and precise biomarkers extraction.

Main Technologies
Machine Learning

Lead SME
Qubiotech Health Intelligence S.L. - Spain

Healthcare partner
Fundación Biomédica Galicia Sur Established In, Hospital Álvaro Cunqueiro - Bloque Técnico - Spain

Data Driven post COVID-19 Rehabilitation
DDRehab aims at deploying a system for remote physical and cognitive rehabilitation of long-lasting coronavirus patients through the use of a smartphone. The solution merges different sets of clinical data to design and to adapt a personalised rehabilitation plan, which will be piloted with 50 patients.

Challenge #6 Recovery

Lead SME
Ab.Acus srl - Italy

Healthcare partner
The Valduce Hospital - Villa Beretta - Italy

Post-Acute Covid Recovery Monitoring & Optimization
Detects and prioritizes resources on patients at high risk of experiencing long-COVID post-discharge. It monitors and supports these patients remotely with the appropriate health interventions. And it helps to better understand how to prevent and treat the long-term effects of COVID-19.

Challenge #6 Recovery

Lead SME
Collaborate Healthcare P.C. - Greece

Healthcare partner
Papageorgiou General Hospital - Greece

Objective Measurements Monitoring of Long COVID-19 Recovery
Provides remote monitoring of patients’ condition, performing daily respiratory measurements at home, to understand the impact on their lung function quality of life.

Challenge #6 Recovery

Main Technologies
IoT, connected medtech, AI, remote monitoring

Lead SME
Arete Medical Technologies Ltd - UK

Healthcare partner
Amsterdam University Medical Centers - The Netherlands

AIDA – Artificial Intelligence for personalizeD recovery support of long covid pAtients
Supports COVID-19 survivors affected by fatigue and mental health symptoms of anxiety and depression. It aims at supporting self-management, including promotion of mental health resilience and physical activity, while providing Patient-Generated Data and PROs to clinicians involved in the care of those patients.

Challenge #6 Recovery

Lead SME
Salumedia Labs SLU - Spain

Healthcare partner
Institut Universitari d’Investigació en Atenció Primària (IDIAP Jordi Gol) - Spain

KAMU Digital Biomarker Based Covid-19 Recovery Screener
A recent study shows almost a third of recovered Covid-19 patients in the UK end up hospitalized again within 5 months of discharge, and one in eight die. KAMU Health, in collaboration with Finnish Lung Health Association, will adapt and productise KAMU’s existing system into a tool that can be used for remote monitoring of patients after hospitalization. The service detects biomarkers for deterioration of the patient’s condition in order to identify those who require professional intervention.

Open challenge

Lead SME
KAMU Health Ltd - Finland

Healthcare partner
Finnish Lung Health Association (FILHA) - Finland
Helsinki University Hospital (HUS) - Finland

vidAVo fIghts At The Edge
There is a lack of patients’ continuous remote monitoring during hospitalization given the fact that this kind of equipment is expensive and has limited mobility. The proposed solution performs low-cost real-time detection of health deterioration and enables highlighting the most critical Covid-19 cases exploiting edge computing.

Open challenge

Lead SME
VIDAVO S.A - Greece

Healthcare partner
Aristotle University of Thessaloniki (AUTH) - Greece