PERFORMANCE COMPARISON OF WORDPRESS POSTS AND MYSQL DATABASE

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TITLE
PERFORMANCE COMPARISON OF WORDPRESS POSTS AND MYSQL DATABASE

AUTHOR(S)
Dijana Stojić1*, Dejan Vujičić1, Đorđe Damnjanović1, Dušan Marković2

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/GNOI2010

DOWNLOAD
https://unitechsp.tugab.bg/images/2024/4-CST/s4_p146_v2.pdf

How to cite this article:
Dijana Stojić1*, Dejan Vujičić1, Đorđe Damnjanović1, Dušan Marković2, PERFORMANCE COMPARISON OF WORDPRESS POSTS AND MYSQL DATABASE, UNITECH – SELECTED PAPERS - 2024

APPLICATION OF THE YOLO ALGORITHM IN THE AUTOMATED DETECTION OF KIDNEY STONES FROM MEDICAL IMAGING DATA

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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

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