Developing an AI-integrated System for X-ray Imaging to Detect Pneumonia and Fractures Using DL (Deep Learning) Techniques (Comprehensive Journal of Science, 2025)
This study aims to develop an integrated artificial intelligence system in conjunction with X-ray imaging devices for the accurate and efficient diagnosis of common medical conditions, such as pneumonia and bone fractures. The proposed system leverages advanced deep learning techniques, particularly convolutional neural networks (CNNs), implemented through the Tensor Flow library. In addition, a user-friendly and interactive interface has been designed using Python programming language and the PyQt6 framework, facilitating seamless interaction between healthcare professionals and the AI system. The integration of AI-driven diagnostic capabilities with X-ray imaging is expected to enhance diagnostic precision, reduce human error, and optimize clinical workflow, ultimately contributing to improved patient outcomes and more efficient healthcare delivery.
Keywords: Artificial Intelligence (AI), X-ray, Deep Learning (DL), Convolutional Neural Networks (CNN), Pneumonia Detection, Fracture Detection, Tensor Flow, PyQt6, ResNet-50, MURA, CheXNet, Image Processing.