On June 29, 2026, MSc candidate Anesa Abazović successfully defended her thesis entitled “Machine Learning and AI Model Development for Medical Applications” within the Artificial Intelligence Master’s programme at the University of Donja Gorica. Through its support for the programme, mentoring activities, and development of competencies in artificial intelligence and high-performance computing, NCC Montenegro contributes to preparing young researchers to apply advanced AI methods in medicine and other socially relevant domains. The thesis investigates the application of machine learning and deep learning to medical image analysis and clinical data classification, while also considering the technical, ethical, and practical challenges of integrating AI systems into healthcare.
Ms Anesa Abazovic during her MSc defence
ABSTRACT – This thesis explores the potential of machine learning (ML) and deep learning (DL) models in the detection of ovarian cancer and the prediction of pneumonia. In the first part, a YOLO model was used to identify tumor lesions in medical images, while in the second part, XGBoost, Random Forest, and neural network models were applied for the classification of clinical data. Model performance was evaluated using metrics such as precision, recall, accuracy, specificity, F1-score, ROC-AUC, MCC, mAP50, and mAP50-95. The experimental analysis demonstrated that AI models can achieve promising performance in both clinical scenarios, with certain limitations that require further validation. In addition to technical aspects, ethical considerations were also examined, including model interpretability, data privacy, and the integration of AI systems into healthcare information systems. It is concluded that AI can provide significant support to modern diagnostics, with the need for further improvements and clinical validation.
On June 29, 2026, MSc candidate Nikola Kavarić successfully defended his thesis entitled “Synergy of Computer Vision and Natural Language Processing in Tuberculosis Diagnostics and Education” within the Artificial Intelligence Master’s programme at the University of Donja Gorica. Through its support for the programme, mentoring activities, and development of competencies in artificial intelligence and high-performance computing, NCC Montenegro contributes to preparing young researchers to develop interdisciplinary AI solutions for healthcare. The thesis investigates the combination of computer vision and Retrieval-Augmented Generation approaches for detecting signs of tuberculosis and providing educational explanations of medical findings.
Mr. Kavaric during his MSc defence (NCC Montenegro)
ABSTRACT – The aim of this thesis is the development and evaluation of a system that combines computer vision and Retrieval-Augmented Generation (RAG) models for the automatic detection of signs of tuberculosis in chest X-ray images and the educational explanation of findings. The initial hypothesis was that it is possible to develop a functional prototype capable of recognizing pathological changes in X-ray images and generating informative, literature-grounded responses for users. Within this research, a CNN model for binary classification and YOLO models for the localization of pathological changes were developed and evaluated. The CNN model achieved an accuracy of 97% on the test set, representing a solid and measurable contribution. The YOLO models adequately demonstrated the concept of localization, with certain limitations related to dataset size and class imbalance. In addition to the visual module, a RAG prototype was implemented, utilizing a local medical document base to generate responses to user queries. The integration was implemented at the prototype level, without clinical validation. Based on the obtained results, the hypothesis was partially confirmed — to a significant extent for the CNN classification component within the test dataset used, while the YOLO and RAG components, due to dataset limitations and the absence of expert-verified reference answers, should be treated as proof-of-concept components. The thesis demonstrates that a modular combination of these technologies can serve as a useful foundation for the development of educational tools in the field of medical diagnostics.
The AI-AGE project was presented at the round table “Artificial Intelligence in Healthcare – Challenges and Opportunities”, held on 24 April 2026 at the Montenegrin Academy of Sciences and Arts (CANU) in Podgorica. The event gathered experts from Montenegro and Bosnia and Herzegovina to discuss the role of AI in healthcare, including clinical applications, digital transformation, ethics, medical imaging, NLP, and AI assistants.
AI-AGE presented at CAN Round Table
AI-AGE was presented by Prof. Dr Nataša Popović, Faculty of Medicine, University of Montenegro, in the session dedicated to AI in clinical practice. The presentation highlighted key findings of the project and demonstrated how AI can support early detection and screening of chronic diseases, including examples related to colorectal cancer detection and the use of biomarkers.
Opportunity to present goals and results of the project
The event was also an opportunity to promote EuroCC activities and the role of NCC Montenegro in strengthening national capacities in HPC, HPDA, and AI. Participation in this round table further positioned AI-AGE within the broader regional discussion on responsible and clinically relevant use of artificial intelligence in medicine.
Key findings and potential benefits of the use of AI models developed in AI-AGE
High-Performance Computing (HPC) and Artificial Intelligence (AI) are rapidly transforming the landscape of healthcare — moving far beyond research prototypes into solutions that can shape clinical practice and improve patient outcomes. This transition from strategy to real-world impact was the focus of the recent EuroCC2 initiative “Symposium: HPC and AI Driven Innovation in Healthcare”. AI-AGE team participated in organization, coordination, and presentations at this event.
Click to watch video
The Vision: Bridging Strategy and Clinical Practice
The event was organized in cross-collaboration with EuroCC2 & EuroCC4SEE
AI-AGE project was presented and further collaboration with EuroCC3 was discussed
Healthcare is today generating vast volumes of data — from medical imaging to electronic health records, genomics, wearable sensors and beyond. HPC provides the computational power needed to process and analyse this data at scale, while AI techniques such as deep learning unlock patterns that are invisible to traditional analysis methods. Together, HPC and AI form a powerful synergy for healthcare innovation:
Accelerated diagnostics: AI models trained on large annotated datasets can assist clinicians by accurately identifying disease signs in imaging and other modalities.
Biomarker discovery and precision medicine: High-throughput computing enables the discovery of subtle biological signals indicative of disease progression or treatment response.
Predictive and personalised care: HPC-enabled AI workflows can predict patient outcomes and support real-time clinical decision making.
Symposium included presentations of successs stories from the region
This strategic capability — from data to insights to impact — was the core theme explored through EuroCC2 activities in Montenegro and the wider South-Eastern Europe region.
Key Takeaways for Healthcare Innovation
From Research to Clinical Utility HPC and AI solutions are no longer confined to laboratories. With appropriate infrastructure, data governance and clinical integration pathways, these technologies are being translated into tools that support healthcare professionals in diagnosis and treatment.
Regional and Cross-Institutional Collaboration The EuroCC2 framework — including the National Competence Centre Montenegro — brings together academic institutions, healthcare providers, and technology partners to share resources, expertise, and training. These collaborative ecosystems are essential for building sustainable HPC-AI capacity in healthcare.
Capacity Building and Skills Development One of the crucial pillars of impactful HPC and AI adoption is training. Workshops, seminars, and hands-on sessions equip researchers, clinicians, and students with the skills to leverage HPC and AI tools effectively in their domains.
Enabling Infrastructure Access Through EuroCC2 and related programmes, researchers and practitioners gain access to European HPC resources — reducing barriers to entry for high-end computing and enabling complex analyses that were previously impractical.
What This Means for Montenegro and Beyond
Montenegro, alongside partner regions across Europe, is building the foundation for a healthcare ecosystem that integrates HPC and AI into everyday clinical workflows. By investing in strategic computing infrastructure, enabling cross-sector collaboration, and fostering technical expertise, the potential to improve patient outcomes, streamline clinical processes, and support data-driven medicine is growing stronger.
The event gathered representatives from Healthcare and IT sectors already involved in research and development of HPC and AI driven solutions for healthcare and medical research. More info at NCC Montenegro site: [link].
Over 20 participants in the Symposium, important discussion of next steps
High-Performance Computing (HPC) and Artificial Intelligence (AI) are increasingly moving beyond research laboratories into real clinical environments. Across Montenegro and the SEE region, promising AI solutions have been developed for medical image analysis, biomarker detection, and predictive diagnostics. The critical challenge today is ensuring their structured transition from research prototypes to validated, deployable tools within healthcare systems.
Symposium on HPC and AI in Healthcare and Medicine co-organiozed by Ai-AGE
This event addresses precisely that transition. It focuses on how HPC infrastructure, interdisciplinary collaboration, and coordinated ecosystem support can accelerate the integration of AI into everyday clinical practice. Particular attention will be given to available computational capacities, real-life use cases, and pathways toward sustainable deployment.
The event is organized as a joint initiative between NCC Montenegro and NCC Bosnia and Herzegovina, within the broader framework of EuroCC 2 and EuroCC4SEE. It also represents a form of cross-project pollination with the AI-AGE project, demonstrating how research-driven innovation can evolve into applied healthcare solutions through regional cooperation.
AI-AGE will be featured in the presentation session
Researchers, clinicians, innovators, and industry partners are invited to join the discussion, exchange expertise, and contribute to shaping the next steps for HPC- and AI-driven healthcare across Southeast Europe. The event is scheduled for Friday, 13 Feb 2026. Please contact NCC Montenegro for further details.
We are proud to share a newly published paper co-authored by an AI-AGE researcher within the Horizon 2020 RECOGNISED consortium in DIABETOLOGIA. This research resulted from collaboration of leading European experts in diabetes, diabetic retinopathy and cognitive impairment. The study shows that retinal neurodysfunction is linked to mild cognitive impairment in people with type 2 diabetes, reinforcing the concept of the retina as a window into brain health.
Beyond its scientific findings, the project marks an important step in strengthening international research infrastructure. Our team helped implement rigorous Good Clinical Practice standards and harmonised imaging and cognitive assessment protocols across multiple European centres — groundwork essential for future large, high-quality datasets suitable for AI-driven discovery of early, non-invasive biomarkers of aging and multimorbidity. This collaboration advances the AI-AGE mission to expand cross-border research capacity and supports ethically robust, standardised big-data research in aging and diabetes. Link to paper: https://doi.org/10.1007/s00125-025-06664-4
The FFplus Innovation Studies Open Call is now open, offering European SMEs and start-ups a focused opportunity to develop and validate generative AI (GenAI) solutions using large-scale European supercomputing resources. The call opens on 3 February 2026 and targets early-stage, high-impact projects with a clear proof-of-concept orientation.
Click to open application website
Coordinated by HLRS (High-Performance Computing Center Stuttgart), FFplus supports innovation at the intersection of AI and HPC, enabling companies to overcome computational barriers and scale beyond conventional cloud or on-premise infrastructures.
Feel free to check with NCC Montenegro for help with the application.
Key facts
Funding: up to €300,000 per project
Deadline: 25 February 2026 (or earlier if 250 proposals are submitted)
Researchers from AI-AGE actively participated in the cross-NCC meeting in Sarajevo, held on 26-27 November under the auspices of the EuroCC4SEE initiative. During this gathering — organized by NCC Montenegro and NCC Bosnia & Herzegovina — colleagues from across Southeast Europe exchanged expertise in high-performance computing (HPC), AI, and regional collaboration, reaffirming our shared commitment to advancing HPC/AI capacity in the region.
AI-AGE researchers participated in the EuroCC4SEE meeting in Sarajevo
The participation of AI-AGE researchers in this forum not only strengthens the link between our aging-biomarker research and HPC/AI infrastructure, but also opens new opportunities for collaboration, knowledge exchange, and access to regional HPC resources. We believe this cooperation will significantly benefit ongoing and future AI-AGE projects, ultimately accelerating innovation in AI-driven biomedical research.
We discussed the potential collaboration and presented AI-AGE efforts
The AI-AGE team held an online meeting to discuss ongoing work with the UK Biobank and data access for retinal imaging analysis. Team members reviewed progress on obtaining RAP login credentials and explored existing repositories of annotated fundus photographs to support AI-based quality differentiation. Collaboration between Dejan, Ivan, and Isidora will focus on identifying suitable datasets and pre-trained models for future algorithm development. This meeting marks an important step toward integrating real-world clinical data into AI-AGE research workflows.
Data gathered from UK Biobank participants (soruce: UK Biobank)
Successful presentation and from Dejan Babic from University of Donja Gorica at the EuroCC4SEE Seminar organized by NCC Turkiye. This was a part of the EuroCC4SEE project, five countries – Türkiye, Serbia, Montenegro, North Macedonia, and Bosnia and Herzegovina – have joined forces to present an engaging online seminar series titled: “5 Beats of Intelligence: AI Meets Diverse Domains”.
Successful presentation at the Seminar series, around 25 attendees
More details on schedule of seminar presentations and and registrations can be accessed at NCC Turkiye website at the foillowing link.
The presentation covered use cases from the AI-AGE project implemented at UDG with NCC support
