Advancing Medical Research with UK Biobank and Retinal Biomarkers

The UK Biobank is a world-renowned resource, housing comprehensive health and genetic data from over 500,000 participants. This invaluable platform is revolutionizing medical research by providing researchers access to detailed medical, lifestyle, and imaging data, driving breakthroughs in understanding and treating diseases like cancer, dementia, and other chronic illnesses.

Advancing Medical Research with UK Biobank

🌟 Key Project Highlight:
One of the pivotal research initiatives, “Exploring the Link Between Dementia and Cancer: Retinal Biomarkers as Predictors of Colon Cancer and Dementia”, is uncovering how retinal biomarkers can serve as early predictors for both colorectal carcinoma and Alzheimer’s disease. By analyzing microvascular complexity in retinal fundus images, this project seeks to identify patterns that could enhance early diagnosis and patient care. Learn more at [link]

Inspired by the RECOGNISED Project:
This initiative builds on insights from the EU-funded RECOGNISED project, which explores the connection between retinal health, cognitive dysfunction, and the risk of dementia in individuals with type 2 diabetes. RECOGNISED has demonstrated the immense potential of retinal imaging as a tool to understand and address chronic diseases. More on RECOGNISED project at [link]

Together, these projects exemplify how innovative approaches and global collaboration can transform healthcare by addressing pressing challenges and improving early detection strategies.

💡 Retinal biomarkers are unlocking new possibilities in personalized medicine and preventive care—advancing our fight against complex diseases.

In-house HPC infrastructure update

As planned, our project AI-AGE is advancing high-performance computing (HPC) infrastructure to support AI-driven research on biomarkers of aging in medical applications. This initiative will empower our team with cutting-edge resources, allowing us to enhance our capacity for data analysis and predictive modeling. To meet the demands of sophisticated AI computations, with the support of AI-AGE, we are upgrading our existing HPC setup with a powerful computing node. This new addition includes a rack computing node equipped with a 48 CPU cores with 128GB RAM, NVIDIA L40 48GB GPUs, and 2x480GB internal SSDs. In addition, the project supported NAS storage of 24TB (multiple disks with RAID) dedicated for dataset management. This infrastructure enhancement is designed to integrate smoothly with our existing equipment, augmenting both our computational and storage capabilities while providing significant value for our investment.

New computing infrastructure supported by the AI-AGE project as planned

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.

The equipment upgrade include a Computing node and NAS storage for data menagement

Research Topic Proposal Defense for the Doctoral Dissertation

The public defense of the Research Topic Proposal for the Doctoral Dissertation by candidate Dr. Isidora Rubežić Lukić, titled “Methods for Assessing Biological Age and Their Correlation with Morbidity and Frailty Syndrome,” took place on September 24, 2024, at the Faculty of Medicine, University of Montenegro, before a committee consisting of:

  • 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.

Dr. Isidora Rubežić Lukić successfuly defended her research topic proposal for her PhD thesis

Initial recruitment of patients for the AI-Age project is completed

The initial recruitment of the patinets for the AI-Age project is finalized. It was conducted in the primary health care clinics of the Podgorica, the capital of Montenegro. We aim to compare the populations of Great Britain and Montenegro in terms of multimorbidity and frailty status, taking into account differences in economic status and life expectancy (80.7 years in the UK, 76.3 in Montenegro).

The recruitment of the patient for the projects completed.

Awakening the vision at UDG: lectures and workshops for new students

AI-AGE team participated in presenations during the implementation of the “Awakening the vision at UDG 2024”. We gave several presentations and workshops relevant to the AI and need to understend and adopt the AI in everyday’s life and workflow. Please check out the video about the event that engaged about 1000 new students enrolled in the first year of studies at UDG.

Awakening the Vision at UDG
Several AI related workshops offered to around 1000 new students at UDG
Participation in lectures and discussions on AI in everyday’s life and workflow

Announcement of the preliminary defense of PhD thesis

Isidora Rubežić – Lukić, MD, will publicly present the goals and expected results, as well as present the research program with the conditions for the successful completion of the doctoral thesis entitled: “Methods for the assessment of biological age and their correlation with morbidity and frailty syndrome”. This preliminary defense will take place in the Meetin Room, Faculty of Medicine, before the Committee for the Evaluation of Doctoral Dissertation Applications, consisting of:

  • 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
Assessing the biological age, multimorbidity and fragility syndrome by analyzing fundus photographs

FFPlus Open Calls for Innovation Studies and Business Experiments

This FFplus open call for the development of generative AI models (“innovation studies“) )addresses the needs of SMEs and Start-ups proficient in generative AI and HPC for large-to extreme-scale computing resources. The strategic objective is to facilitate and strengthen the technological development of European SMEs in the area of generative AI. The participating SMEs and Start-ups will be supported in enhancing their innovation potential by leveraging new generative AI models, such as Large Language Models (LLMs), building on their existing expertise, application domain, business model and potential for expansion. Link: https://www.ffplus-project.eu/en/open-call/innovation-studies/

Open Call for Innovation Studies

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/

Open Call for Business Experioments
Click on image to learn more about FFPlus

 

Over 1000 visitors in the first 6 months

It has been little bit over a 6-month period since we started the project website. Early stats indicate that there is an interest in the project. The statistcs has already recorded over 1000 visitors. Lots of this is thanks to the participation in live events and conferences, social media, and inter-project collaboration.

It has been over 6 months of the website uptime
The statistics for the website shows a growing interest in the project activity

Advancing Research on Chronic Diseases in the Elderly at the Faculty of Medicine, University of Montenegro

The Faculty of Medicine at the University of Montenegro is at the forefront of tackling some of the most pressing health challenges faced by the elderly population. Through innovative research and collaboration, the Faculty is driving progress in understanding and addressing chronic diseases associated with aging.

Advancing Research on Chronic Diseases in the Elderly in Montenegro

📌 Key Projects:
1️⃣ AI-AGE Project
Launching in 2024, the Artificial Intelligence Supported Identification of Novel Non-Invasive Biomarkers of Aging aims to build scientific and innovation capacity in aging biomarkers. Supported by the Ministry of Science of Montenegro, this project utilizes cutting-edge AI technology to advance aging research.

2️⃣ RECOGNISED Project
Spanning from 2020 to 2024, the Retinal and Cognitive Dysfunction in Type 2 Diabetes project explores the links between retinal health, cognitive impairment, and dementia risk in individuals with type 2 diabetes. This initiative is pivotal in mitigating diabetes-related complications in aging populations. [link]

3️⃣ DEMONSTRATE Project
Running from 2019 to 2021, New Methods for Risk Stratification for Cancer and Alzheimer’s Disease Progression in Patients in Montenegro focused on innovative strategies to assess progression risks for these critical conditions.

Why It Matters:
These projects underscore the Faculty’s commitment to advancing medical research that improves healthcare outcomes for the elderly. By addressing chronic diseases and leveraging innovative approaches, the Faculty of Medicine is contributing to healthier aging and stronger healthcare systems.

🌍 Together, we are shaping a future where science and innovation meet to tackle the challenges of aging populations.

Symorg 2024 Conference

A research paper prepared by our young researcher was published at the SymOrg 2024 conference, organized by the Faculty of Organizational Science, University of Belgrade, at Zlatibor, Serbia on June 12-14, 2024. The conference, traditionally envisioned as a platform for knowledge innovation and empirical research, bringing together representatives from the scientific and professional community, was themed: ”Unlocking The Hidden Potential Of Organization Through Merging Of Humans And Digitals”, aiming to address the newfound need for balance in the era of AI. This paper was done with the support of EUROCC2 and NCC Montenegro team.

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.