Adaptive algorithms for linking databases in clinical settings and identifying health indicators

信息和计算技术的进步使有效和高效的软件分析工具得以开发，这些工具可以连接和更新具有复杂和不同性质的大型数据库。然而，在医疗保健和公共卫生环境中，这方面的好处还没有完全实现，总体上对健康结果产生了负面影响。可用于为医疗保健和公共卫生应对措施提供信息的数据库支持工具对于提供有效的临床和危重护理服务至关重要，特别是在新出现和再次出现的传染病对人类健康构成持续威胁的时候。约克大学疾病建模中心的感染和免疫建模实验室将与HealthWizer合作，开发一套用于连接数据库的自适应算法。将使用该套房

Advances in information and computational technologies have enabled the development of effective and efficient software analytic tools that can link and update large databases of complex and heterogeneous nature. The benefits of this, however, have not been fully realized within the healthcare and public health settings, negatively affecting health outcomes in general. A database support tool that can be used to inform healthcare and public health responses will be crucial to the provision of effective clinical and critical care delivery, especially in times where emerging and re-emerging infectious diseases pose continuous threats to human health. The Modelling Infection and Immunity Lab in the Centre for Disease Modelling at York University will work with HealthWizer to develop a suite of adaptive algorithms for linking databases. The suite will be used