Artificial intelligence (AI) has the potential to revolutionize diagnostic imaging, leading to significant improvements in efficiency, accuracy, and patient outcomes. Artificial intelligence (AI) in diagnostic imaging signals the beginning of a revolutionary period in healthcare, characterized by previously unresolved gains in perception and effectiveness. The paper explores how AI addresses longstanding challenges in the field, including human error, time-consuming manual processes, and subjective image interpretation. The paper employed a systematic literature review to assess the impact of AI on diagnostic imaging efficiency and accuracy. Studies published between 2019 and 2023 were reviewed, focusing on peer-reviewed journals and conference proceedings. The initial portion of the paper provides an overview of the classic difficulties associated with diagnostic imaging, such as the possibility of human mistakes, the laborious manual processing process, and the subjective interpretation of pictures. The paper examines how artificial intelligence (AI) technologies are effective diagnostic imaging techniques and how they may improve efficiency and accuracy in clinical settings. By leveraging machine learning techniques like convolutional neural networks (CNNs), AI can analyze complex imaging data with exceptional precision, enabling early disease detection, improved risk assessment, and more timely diagnoses. The paper also discusses challenges associated with AI implementation, such as algorithm interpretability and data privacy. In conclusion, thoughtful integration of AI holds immense promise for transforming diagnostic imaging into a new era of precision medicine.
Kanagala Anusha (Wed,) studied this question.