Thesis Abstract

Abstract
This thesis explores the role of Artificial Intelligence (AI) in enhancing diagnostic accuracy in radiography. With the rapid advancements in technology, AI has emerged as a promising tool in the field of healthcare, particularly in medical imaging. The integration of AI algorithms with radiography has the potential to revolutionize the way medical images are interpreted, leading to more accurate and timely diagnoses. This research aims to investigate the impact of AI on diagnostic accuracy in radiography and to identify the challenges and opportunities associated with its implementation. The study begins with a comprehensive review of the literature, examining the current state of AI in radiography and its potential benefits. The literature review highlights the various AI algorithms and techniques that have been developed specifically for medical imaging, as well as the challenges faced in integrating AI into clinical practice. By analyzing existing studies and research findings, this section provides a foundation for understanding the significance of AI in improving diagnostic accuracy in radiography. The research methodology section outlines the approach taken to investigate the research questions posed in this study. Utilizing a mixed-methods approach, quantitative data will be collected from radiography departments that have adopted AI technology, while qualitative data will be gathered through interviews with radiologists and AI experts. The methodology also includes the process of data analysis and interpretation, ensuring the validity and reliability of the findings. The discussion of findings section presents the results of the study, including the impact of AI on diagnostic accuracy in radiography, the challenges faced in implementing AI technology, and the perspectives of radiologists and AI experts on the use of AI in medical imaging. The findings shed light on the potential benefits of AI in improving diagnostic accuracy, such as faster image analysis and reduced interpretation errors, as well as the limitations and ethical considerations associated with AI integration. In conclusion, this thesis summarizes the key findings and implications of the study, emphasizing the role of AI in enhancing diagnostic accuracy in radiography. The recommendations provided aim to guide future research and clinical practice in harnessing the full potential of AI technology in medical imaging. Ultimately, this research contributes to the ongoing discourse on the transformative impact of AI on healthcare and radiography, paving the way for more efficient and effective diagnostic processes. Keywords Artificial Intelligence, Radiography, Diagnostic Accuracy, Medical Imaging, Healthcare Technology, Data Analysis, Research Methodology.

Thesis Overview