RÉSUMÉ
Objective To understand the effectiveness evaluation research of tumor MDT,and analyze the development status and differences of evaluation tools at home and abroad,to provide reference for the subsequent summary evaluation and continuous improvement of tumor MDT,and the strengthening of MDT supervision.Methods Four literature databases at home and abroad were searched to obtain relevant literatures,and literature screening and systematic review were conducted.Results A total of 87 literatures were included,including 26 literatures in Chinese and 61 literatures in English;the most published years were 2020;the main countries of the first authors were the UK.Foreign evaluation tools focus on the key elements of structure and process,while evaluation systems in China focus on the index content at the result level.Conclusion In China,the scientific and comprehensive selection of tumor MDT evaluation indicators needs to be improved,the analysis of influencing factors on the structure and process of MDT needs to be strengthened,and the extrapolation of the existing evaluation systems need to be verified.It is suggested to strengthen the evidence support of evaluation index selection,attach importance to the evaluation of process links,promote the in-depth study of the influencing factors of tumor MDT,and further encourage the empirical application of the existing evaluation system.
RÉSUMÉ
With the development of digital technology， an increasing number of artificial intelligence （AI） technologies are being applied in the field of public health， significantly improving the efficiency of healthcare systems. However， such technological advancement also introduces a series of ethical risks. In this article， we conducted a systematic review by searching nine domestic and international databases and analyzing the ethical issues related to AI in public health， ultimately including 158 articles. Based on the analysis of the included literature， ethical risks were categorized into four aspects： data， algorithms， rights and responsibilities， and social impact. A total of 15 key issues were identified， among which privacy and confidentiality， informed consent， data security， and fairness， justice and inclusion emerged as the most prominent issues. The ethical challenges posed by AI in the field of public health cannot be ignored， and it is necessary to formulate ethical guidelines and practical recommendations for AI in this field， establish sound regulatory and review mechanisms， thereby ensuring the healthy development of AI research in public health.