Current status and future prospects of the application of artificial intelligence in clinical practice - LI Xinyu; YUAN Qian; ZHU Fenglei; YANG Tao (Zhongguo linchuang yanjiu)
The technological innovation of artificial intelligence (AI) is reshaping the paradigm of practice in the medical field. AI methods such as machine learning and deep learning, have shown great potential in areas like disease diagnosis and early screening, treatment plan recommendations, drug development, and clinical trials, significantly improving the efficiency of clinical medical research and services. At the same time, issues have emerged, such as the value conflict between medical data privacy protection and the need for cross - institutional sharing, the theoretical opposition between the "black box "nature of algorithms and the principle of clinical decision-making transparency, and the dilemma of unclear responsibility in cases of AI- assisted diagnosis and treatment errors. This paper reviews the progress of AI applications in clinical medicine, analyzes and summarizes the opportunities and challenges faced, and proposes future trends and research directions, aiming to provide insights for AI research and applications in clinical medicine.