Thesis Abstract

Abstract
The integration of artificial intelligence (AI) in radiography has revolutionized the field of medical imaging, enhancing diagnostic accuracy and clinical outcomes significantly. This thesis explores the application of AI in radiography with the primary objective of improving diagnostic accuracy. The study delves into the background of AI in healthcare, outlining its potential benefits and challenges. By addressing the problem statement of the limitations of traditional radiographic interpretation methods, this research aims to provide a comprehensive analysis of the impact of AI on diagnostic accuracy in radiography. The research methodology employed in this study encompasses a detailed literature review of existing studies on AI in radiography, highlighting key findings and advancements in the field. Through a systematic review of relevant literature, this thesis identifies ten critical areas where AI has been successfully applied to enhance diagnostic accuracy in radiography. The literature review also explores the various AI algorithms and technologies utilized in radiography, shedding light on their effectiveness in improving diagnostic precision. Chapter four of this thesis presents a comprehensive discussion of the findings, emphasizing the significant role of AI in enhancing diagnostic accuracy in radiography. By analyzing the results of previous studies and current advancements in AI technology, this chapter provides valuable insights into the potential of AI to revolutionize radiographic interpretation. In conclusion, this thesis highlights the significance of integrating AI into radiography for improved diagnostic accuracy. By leveraging AI algorithms and technologies, radiographers can enhance their diagnostic capabilities, leading to more accurate and timely patient diagnoses. The findings of this study underscore the importance of embracing AI in radiography to optimize patient care and clinical outcomes. Keywords Artificial Intelligence, Radiography, Diagnostic Accuracy, Medical Imaging, Healthcare, Machine Learning. (Word Count 200 words)

Thesis Overview

The project titled "Application of Artificial Intelligence in Radiography for Improved Diagnostic Accuracy" aims to explore the integration of artificial intelligence (AI) technologies in radiography to enhance diagnostic accuracy in medical imaging. This research overview highlights the importance of this study in the field of radiography and healthcare. Radiography plays a crucial role in diagnosing and monitoring various medical conditions through the use of imaging techniques such as X-rays, CT scans, and MRIs. However, interpreting these images accurately can be challenging, requiring specialized training and expertise. With the advancements in AI technologies, there is a growing interest in leveraging machine learning algorithms to assist radiologists in analyzing and interpreting medical images more efficiently and accurately. The primary objective of this project is to investigate how AI can be applied in radiography to improve diagnostic accuracy. By training AI models on large datasets of medical images, the research aims to develop algorithms that can assist radiologists in detecting abnormalities, identifying patterns, and making more accurate diagnoses. This study will also explore the potential benefits and challenges of implementing AI in radiography, including issues related to data privacy, algorithm bias, and regulatory compliance. Furthermore, the project will involve conducting a comprehensive literature review to understand the current state of AI applications in radiography and identify gaps in existing research. The research methodology will include collecting and analyzing relevant data, developing AI models, and evaluating their performance in comparison to traditional diagnostic methods. The findings of this study will contribute to the growing body of knowledge on the use of AI in healthcare and provide insights into the potential impact of AI on the future of radiography practice. In conclusion, the project on the "Application of Artificial Intelligence in Radiography for Improved Diagnostic Accuracy" holds significant promise in revolutionizing the field of radiography by enhancing diagnostic capabilities and improving patient outcomes. By integrating AI technologies into radiology workflows, healthcare providers can potentially streamline diagnostic processes, reduce errors, and ultimately improve the quality of patient care.