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.
