Another AI and S3 related project is granted for implementation at UDG. The AI-AGE project proposes the use of machine learning (ML) algorithms and evaluation of state-of-the-art AI tools to train and create prediction models to identify novel non-invasive biomarkers of aging, and increased risk for development of age-related conditions. The idea is to utilize a large dataset of annotated retinal images from the UK Biobank, to explore deep learning (DL) techniques, most commonly based on convolutional neural networks (CNNs), such as U-Net and Res-Net, and transformers, but also to expand the research on the use of ensemble methods that combine ML techniques to improve performance and accuracy.
This project is a result of sustainability efforts by NCC Montenegro team and collaboration betweeb Faculty for information systems at University of Donja Gorica and Faculty of medicine at University of Montenegro.
