TITLE
APPLICATION OF THE YOLO ALGORITHM IN THE AUTOMATED DETECTION OF KIDNEY STONES FROM MEDICAL IMAGING DATA
AUTHOR(S)
Stefan Ćirković*, Katarina Karić, Nikola Stanić
ABSTRACT
Kidney stones are one of the most common urological issues worldwide, and timely diagnosis is crucial for effective treatment and reducing complications. Traditional diagnostic methods, such as ultrasound and computed tomography (CT), require manual interpretation of images by specialists, which can be time-consuming. With the development of artificial intelligence, neural networks are increasingly being applied in medicine. This paper presents the application of the YOLO (You Only Look Once) algorithm on a dataset of medical images for the detection and classification of kidney stones. This approach can serve as support for specialists in making faster and more informed decisions, with the potential to reduce the burden and costs in the healthcare system, but it does not replace professional medical diagnosis.
DOI
http://www.doi.org/10.70456/SHCE4087
DOWNLOAD
https://unitechsp.tugab.bg/images/2024/4-CST/s4_p128_v1.pdf
How to cite this article:
Matija Špeletić, Stevica Cvetković, Milan Protić, Saša V. Nikolić, EXPLORING RAG IN MEDICAL QUESTION ANSWERING: INTEGRATING LLMS AND VECTOR DATABASES, UNITECH – SELECTED PAPERS - 2024