Application of Artificial Intelligence in Radiography: Enhancing Diagnostic Accuracy and Efficiency

Thesis Abstract

Abstract
This thesis investigates the application of Artificial Intelligence (AI) in radiography to enhance diagnostic accuracy and efficiency. The integration of AI technologies into radiography has the potential to revolutionize the field by improving the speed and accuracy of diagnoses, ultimately leading to better patient outcomes. The study begins with an exploration of the current state of radiography and the challenges faced in the diagnostic process. It then delves into the theoretical background of AI and its various applications in healthcare, focusing specifically on radiography. The research methodology section outlines the approach taken to evaluate the impact of AI on diagnostic accuracy and efficiency in radiography. A comprehensive literature review is conducted to examine existing studies and technologies in this area. The study also includes the development and testing of a prototype AI system designed to assist radiologists in interpreting medical images. The findings of this research highlight the significant potential of AI to enhance diagnostic accuracy and efficiency in radiography. The AI system demonstrated promising results in improving the speed and accuracy of image analysis, leading to more timely and accurate diagnoses. The study also identifies some limitations and challenges associated with the implementation of AI in radiography, such as data privacy concerns and the need for ongoing training and support for healthcare professionals. In conclusion, this thesis contributes to the growing body of literature on the application of AI in radiography. By harnessing the power of AI technologies, radiologists can make more informed decisions, leading to improved patient care and outcomes. The study underscores the importance of continued research and development in this area to fully realize the potential benefits of AI in healthcare.