Objective To provide suggestions and a reference for improving the quality management system of clinical trials of therapeutic vaccines and promoting the development of therapeutic vaccines in China.Methods Literature...Objective To provide suggestions and a reference for improving the quality management system of clinical trials of therapeutic vaccines and promoting the development of therapeutic vaccines in China.Methods Literature research,case study and comparative study were used to analyze the quality management system of clinical trials of therapeutic vaccines.Results and Conclusion From the perspective of the sponsor,investigators and the thirdparty technical service company,the problems such as the low efficiency of clinical trial sample preparation and the lax implementation of the protocol by hospital departments in the quality management of clinical trials of therapeutic vaccines in China were found.Then,the optimization plan for the quality management of clinical trials of therapeutic vaccines is proposed,including optimizing the preparation process of therapeutic vaccines and strengthening the training of hospital department personnel.展开更多
农田作为国家的保护土地资源,与农业生产、食品安全、人体健康有着密不可分的关系。因此,研究农田土壤污染状况对确保粮食质量、保护农田资源具有重大意义。传统的农田土壤污染研究多针对单一场景、污染物或实验条件,难以应对日益复杂...农田作为国家的保护土地资源,与农业生产、食品安全、人体健康有着密不可分的关系。因此,研究农田土壤污染状况对确保粮食质量、保护农田资源具有重大意义。传统的农田土壤污染研究多针对单一场景、污染物或实验条件,难以应对日益复杂的环境问题。随着大数据时代的来临,机器学习逐渐在农田土壤环境保护领域中得到广泛应用,并在土壤污染识别、修复等方面的研究中展现其客观、准确、擅长处理复杂任务的优势。本文介绍了常用的机器学习流程、方式、算法和模型性能评价指标;通过对Web of Science以及中国知网数据库中2011—2023年间相关领域文献进行统计分析,从农田土壤污染的识别、修复材料的筛选与机理研究、生态风险评估三方面综述机器学习在这些领域研究中的应用,分析了其优势和局限性。最后,本文从提升数据共享、增强模型可解释性以及应用迁移学习等新手段提高模型性能等方面进行了展望。展开更多
文摘Objective To provide suggestions and a reference for improving the quality management system of clinical trials of therapeutic vaccines and promoting the development of therapeutic vaccines in China.Methods Literature research,case study and comparative study were used to analyze the quality management system of clinical trials of therapeutic vaccines.Results and Conclusion From the perspective of the sponsor,investigators and the thirdparty technical service company,the problems such as the low efficiency of clinical trial sample preparation and the lax implementation of the protocol by hospital departments in the quality management of clinical trials of therapeutic vaccines in China were found.Then,the optimization plan for the quality management of clinical trials of therapeutic vaccines is proposed,including optimizing the preparation process of therapeutic vaccines and strengthening the training of hospital department personnel.
文摘农田作为国家的保护土地资源,与农业生产、食品安全、人体健康有着密不可分的关系。因此,研究农田土壤污染状况对确保粮食质量、保护农田资源具有重大意义。传统的农田土壤污染研究多针对单一场景、污染物或实验条件,难以应对日益复杂的环境问题。随着大数据时代的来临,机器学习逐渐在农田土壤环境保护领域中得到广泛应用,并在土壤污染识别、修复等方面的研究中展现其客观、准确、擅长处理复杂任务的优势。本文介绍了常用的机器学习流程、方式、算法和模型性能评价指标;通过对Web of Science以及中国知网数据库中2011—2023年间相关领域文献进行统计分析,从农田土壤污染的识别、修复材料的筛选与机理研究、生态风险评估三方面综述机器学习在这些领域研究中的应用,分析了其优势和局限性。最后,本文从提升数据共享、增强模型可解释性以及应用迁移学习等新手段提高模型性能等方面进行了展望。
