Application and Development of Artificial Intelligence-based Medical Imaging Diagnostic Assistance System

Abstract

Medical imaging technology plays a key role in modern medical diagnosis and treatment, and the integration of artificial intelligence (AI) technology has revolutionised the field.AI uses deep learning and machine learning algorithms to analyse medical imaging data, improving the accuracy of lesion identification and disease prediction, and thus significantly improving the efficiency of diagnostic work. The scope of application of AI has also expanded to include the optimisation of treatment planning, the prediction of disease progression, and the assessment of patient prognosis. The application of AI has also been extended to the optimisation of treatment plans, prediction of disease progression and assessment of patient prognosis. Although AI shows great potential in medical imaging diagnosis, its clinical application still faces challenges. The quality, accessibility, sensitivity, and privacy of medical image data, as well as the "black box" nature of AI models, pose obstacles to the widespread application of AI technology. In addition, data security and privacy protection are also issues that need to be addressed. This paper reviews the current status of AI application in medical imaging diagnosis, analyses the main problems faced, and discusses the future development direction. Examples of AI applications in different medical imaging fields are discussed in the paper, and challenges such as data quality, laws and regulations, model interpretability and data security are explored in depth, and solution strategies such as enhancing data management, improving model generalisation and interpretability, strengthening data security techniques, and promoting interdisciplinary cooperation are proposed. This paper aims to provide reference for researchers and practitioners of AI in medical imaging diagnosis to promote the healthy development of the field, and calls on experts, scholars, policy makers and technology developers to work together to overcome the challenges and to realize the potential of AI technology in improving the quality and efficiency of healthcare services and safeguarding patients' health.

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