PDF(Pubmed)
Abstract：
BACKGROUND: Artificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring treatments to individual patient conditions. This has heightened the demand for access to diverse data from clinical practice and daily life for research, posing challenges due to the sensitive nature of medical information, including genetics and health conditions. Regulations like the Health Insurance Portability and Accountability Act (HIPAA) in the U.S. and the General Data Protection Regulation (GDPR) in Europe aim to strike a balance between data security, privacy, and the imperative for access.
RESULTS: We present the Gemelli Generator - Real World Data (GEN-RWD) Sandbox, a modular multi-agent platform designed for distributed analytics in healthcare. Its primary objective is to empower external researchers to leverage hospital data while upholding privacy and ownership, obviating the need for direct data sharing. Docker compatibility adds an extra layer of flexibility, and scalability is assured through modular design, facilitating combinations of Proxy and Processor modules with various graphical interfaces. Security and reliability are reinforced through components like Identity and Access Management (IAM) agent, and a Blockchain-based notarisation module. Certification processes verify the identities of information senders and receivers.
CONCLUSIONS: The GEN-RWD Sandbox architecture achieves a good level of usability while ensuring a blend of flexibility, scalability, and security. Featuring a user-friendly graphical interface catering to diverse technical expertise, its external accessibility enables personnel outside the hospital to use the platform. Overall, the GEN-RWD Sandbox emerges as a comprehensive solution for healthcare distributed analytics, maintaining a delicate equilibrium between accessibility, scalability, and security.
RESULTS: We present the Gemelli Generator - Real World Data (GEN-RWD) Sandbox, a modular multi-agent platform designed for distributed analytics in healthcare. Its primary objective is to empower external researchers to leverage hospital data while upholding privacy and ownership, obviating the need for direct data sharing. Docker compatibility adds an extra layer of flexibility, and scalability is assured through modular design, facilitating combinations of Proxy and Processor modules with various graphical interfaces. Security and reliability are reinforced through components like Identity and Access Management (IAM) agent, and a Blockchain-based notarisation module. Certification processes verify the identities of information senders and receivers.
CONCLUSIONS: The GEN-RWD Sandbox architecture achieves a good level of usability while ensuring a blend of flexibility, scalability, and security. Featuring a user-friendly graphical interface catering to diverse technical expertise, its external accessibility enables personnel outside the hospital to use the platform. Overall, the GEN-RWD Sandbox emerges as a comprehensive solution for healthcare distributed analytics, maintaining a delicate equilibrium between accessibility, scalability, and security.
摘要：
背景：人工智能（AI）已成为推进当代个性化医疗的关键工具，目的是根据患者的具体情况定制治疗方法。这增加了对从临床实践和日常生活中获取不同数据进行研究的需求，由于医疗信息的敏感性，包括遗传和健康状况。美国的健康保险流通和责任法案（HIPAA）和欧洲的通用数据保护条例（GDPR）等法规旨在在数据安全之间取得平衡。隐私,以及访问的必要性。
结果：我们介绍了GemelliGenerator-真实世界数据(GEN-RWD)沙盒，为医疗保健中的分布式分析而设计的模块化多代理平台。其主要目标是使外部研究人员能够利用医院数据，同时维护隐私和所有权。消除了直接数据共享的需要。Docker兼容性增加了额外的灵活性，通过模块化设计确保可扩展性，促进代理和处理器模块与各种图形界面的组合。安全性和可靠性通过身份和访问管理(IAM)代理等组件得到加强。和基于区块链的公证模块。认证过程验证信息发送者和接收者的身份。
结论：GEN-RWD沙盒架构实现了良好的可用性水平，同时确保了灵活性的融合，可扩展性，和安全。具有用户友好的图形界面迎合不同的技术专长，它的外部可访问性使医院外部的人员能够使用该平台。总的来说,GEN-RWDSandbox成为医疗保健分布式分析的综合解决方案，在可达性之间保持微妙的平衡，可扩展性，和安全。
结果：我们介绍了GemelliGenerator-真实世界数据(GEN-RWD)沙盒，为医疗保健中的分布式分析而设计的模块化多代理平台。其主要目标是使外部研究人员能够利用医院数据，同时维护隐私和所有权。消除了直接数据共享的需要。Docker兼容性增加了额外的灵活性，通过模块化设计确保可扩展性，促进代理和处理器模块与各种图形界面的组合。安全性和可靠性通过身份和访问管理(IAM)代理等组件得到加强。和基于区块链的公证模块。认证过程验证信息发送者和接收者的身份。
结论：GEN-RWD沙盒架构实现了良好的可用性水平，同时确保了灵活性的融合，可扩展性，和安全。具有用户友好的图形界面迎合不同的技术专长，它的外部可访问性使医院外部的人员能够使用该平台。总的来说,GEN-RWDSandbox成为医疗保健分布式分析的综合解决方案，在可达性之间保持微妙的平衡，可扩展性，和安全。
