AI-AGE project, supported by the Ministry of education, science and innovation, is implemendet through collaboration between Faculty for information systems and technologies at Uiversity of Donja Gorica, and Faculty of medicine at University of Montenegro. The in-house HPC infrastructure is a result of cross-project collaboration with HPC4S3ME project (IPA programme) and both of these project are done with the support from EUROCC NCC Montenegro. The main goal for the in-house lab is for researchers to gain a hands on experience with physical equipment a their disposal, while for larger computing tasks, we will apply for computing time on some of the EU supercomputers.

• Prof. dr Aneta Bošković – Full Professor at the Faculty of Medicine, University of Montenegro, Chair
• Prof. dr Antoaneta Adžić Zečević – Full Professor at the Faculty of Medicine, University of Montenegro, Member
• Prof. dr Nataša Popović, Associate Professor at the Faculty of Medicine, University of Montenegro, Mentor and Member

After the candidate’s presentation, the committee members provided comments and suggestions important for the continuation of her dissertation work and posed questions that the candidate successfully answered. After all comments and suggestions were adequately addressed, the committee unanimously decided that the candidate had successfully defended her doctoral dissertation topic.

• Prof. Dr. Aneta Bošković – full professor of the Faculty of Medicine, University of Montenegro, president
• Prof. Dr. Nataša Popović – associate professor of the Faculty of Medicine, University of Montenegro, mentor-member
• Prof. Dr. Antoaneta Adžić Zečević – associate professor of the Faculty of Medicine, University of Montenegro, member

This announcement is the first call for proposals to address the uptake of HPC by SMEs in order to solve specific business challenges of SMEs that have had no prior use of, or experience with, HPC services. The resulting sub-projects will perform “business experiments” (also referred to just as experiments) that should demonstrate to the broader European SME ecosystem that HPC uptake solves business challenges and leads to positive business impact through the use and deployment of HPC-based computational methods. Thus, their key outputs are success stories that promote, communicate, and disseminate the business impact of HPC uptake to the SME ecosystem. Link: https://www.ffplus-project.eu/en/open-call/business-experiments/

The scientific paper “Detection of Scoliosis” by Elvis Taruh, Enisa Trubljanin, and Dejan Babić explores the application of a deep learning model integrated with a web application to detect scoliosis using x-ray images. Utilizing a dataset of 198 x-ray images from Roboflow, the initial model performance was unsatisfactory, prompting manual annotation of 245 images, which significantly improved the model’s accuracy. YOLOv8, a state-of-the-art object detection algorithm, was used to train two models, demonstrating improved performance with manual annotations. The web application, built with Flask, HTML, CSS, and JavaScript, provides a user-friendly interface for analyzing scoliosis detection results. The backend uses MySQL for data storage and management, facilitating efficient image processing, result display, and feedback from doctors. Evaluation metrics indicate that the second model, which underwent refined annotation and augmentation, performed better, avoiding overfitting and demonstrating higher precision. This approach enhances early scoliosis diagnosis and offers a scalable solution for other medical detection challenges, supporting healthcare providers with more accurate diagnostic tools and improving patient care.