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Personalised prediction
A patient-oriented model designed to study disease progression using relevant clinical and demographic information.
Research • AI • Public Health
COVIDAI
Using artificial intelligence and machine learning to study factors influencing COVID-19 development and to support modelling of disease progression and epidemic dynamics.
About the project
Data-driven approaches to COVID-19
COVIDAI focuses on heterogeneous information such as demographic and clinical data, blood markers, geographical information and medical imaging to develop predictive and epidemiological models.
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Epidemiological modelling
Models can represent the development of an epidemic at population or regional level and examine changes over time.
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Machine learning
Artificial intelligence and machine learning methods are used to analyse complex data and support research workflows.
Research models
Two complementary modelling directions
The project describes both patient-specific disease progression and population-level epidemic dynamics.
Personalized AI Model
A machine-learning approach for monitoring the condition of an infected patient and estimating the likely disease progression over the following days.
Data: demographic information, clinical data, blood-test data and medical imaging.
Epidemiological Model
A compartmental modelling approach for examining the spread and clinical progression of COVID-19 across populations and regions.
Focus: susceptible, exposed, infected, dead and recovered population categories.
AIArtificial Intelligence
MLMachine Learning
X-rayMedical Imaging
SEIRDEpidemiological Modelling
Consortium
Research partners
The COVIDAI project involved academic and clinical partners from Serbia and Croatia.
University of Kragujevac
Project coordination and research activities in Serbia.
kg.ac.rs →Faculty of Engineering, University of Rijeka
Research collaboration and engineering expertise from Croatia.
riteh.uniri.hr →Clinical Hospital Centre Rijeka
Clinical research and medical-data collaboration.
Research output
Publications
Research outputs cover epidemic-curve estimation, medical imaging, semantic segmentation and machine-learning approaches.
COVID-19 Epidemic Curves
Estimation of COVID-19 epidemic curves using genetic programming algorithms.
Lung Condition Assessment
Automatic evaluation of COVID-19 patient lung condition using X-ray images and convolutional neural networks.
COVID-19 Spread Models
Research into regressive artificial intelligence and machine-learning methods for modelling COVID-19 spread.
Contact
COVIDAI Research Project
For project information, research collaboration and related enquiries, please contact the responsible project representatives.
Project information
University of Kragujevac
Serbia
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