Thesis Abstract

Abstract
This thesis explores the potential application of artificial intelligence (AI) in the early detection of diseases through medical imaging. The use of AI in healthcare has shown promise in improving diagnostic accuracy and efficiency. The research aims to investigate how AI technology can be leveraged to enhance the early detection of diseases in medical imaging, ultimately leading to better patient outcomes. The study begins with an introduction outlining the background and significance of the research topic. It then presents the problem statement, objectives, limitations, scope, and significance of the study. The structure of the thesis is also detailed to provide an overview of the subsequent chapters. In the literature review chapter, ten key aspects related to AI in medical imaging and disease detection are critically analyzed. This section provides a comprehensive overview of existing research, technologies, and methodologies in the field, highlighting gaps and opportunities for further investigation. The research methodology chapter outlines the approach and methods employed to investigate the potential of AI in disease detection through medical imaging. It includes details on data collection, AI algorithms, image processing techniques, and evaluation criteria used in the study. The chapter also discusses ethical considerations and potential biases in AI applications in healthcare. The findings chapter presents a detailed analysis and discussion of the results obtained from the research. It highlights the effectiveness of AI in early disease detection, its impact on diagnostic accuracy, and potential challenges encountered during the study. The chapter also includes case studies and examples to illustrate the practical application of AI in medical imaging. In the conclusion and summary chapter, the key findings, implications, and recommendations of the study are summarized. The thesis concludes by discussing the potential future developments and advancements in the field of AI for disease detection in medical imaging. Overall, this research contributes to the growing body of knowledge on the application of AI in healthcare and highlights its importance in improving patient care and outcomes. Keywords Artificial intelligence, Disease detection, Medical imaging, Healthcare, Early diagnosis, Machine learning, Image processing.

Thesis Overview

The project titled "Investigating the potential of using artificial intelligence for early detection of diseases in medical imaging" aims to explore the application of artificial intelligence (AI) in the field of medical imaging for the early detection of diseases. Medical imaging plays a crucial role in diagnosing and monitoring various medical conditions, and the integration of AI technologies has shown great promise in enhancing the accuracy and efficiency of these processes. The research will delve into the current landscape of medical imaging techniques and the challenges faced in traditional disease detection methods. By leveraging AI algorithms and machine learning models, the study seeks to identify patterns, anomalies, and biomarkers in medical images that may indicate the presence of diseases at early stages. This proactive approach could significantly improve patient outcomes by enabling timely intervention and treatment. The project will involve a comprehensive literature review to examine existing studies, methodologies, and technologies related to AI in medical imaging. By synthesizing this information, the research aims to identify gaps in the current knowledge and propose novel approaches or frameworks for leveraging AI in disease detection. Moreover, the research methodology will include the collection and analysis of medical imaging data sets, the development and training of AI algorithms, and the evaluation of their performance in detecting diseases accurately and efficiently. By conducting empirical studies and experiments, the project seeks to validate the effectiveness and reliability of AI-based approaches in early disease detection. The findings of this research are expected to contribute to the growing body of knowledge on the application of AI in healthcare and medical imaging. The potential benefits of using AI for early disease detection include improved diagnostic accuracy, reduced healthcare costs, and enhanced patient care outcomes. By shedding light on the capabilities and limitations of AI technologies in this context, the study aims to provide valuable insights for researchers, healthcare professionals, and policymakers seeking to harness the power of AI for improving healthcare delivery. In conclusion, the project on investigating the potential of using artificial intelligence for early disease detection in medical imaging represents a significant step towards advancing the field of medical diagnostics through innovative technologies. By bridging the gap between AI and healthcare, this research aims to pave the way for a future where early detection and intervention can save lives and improve the quality of healthcare services.