【Author】
Aich, Satyabrata; Sinai, Nday Kabulo; Kumar, Saurabh; Ali, Mohammed; Choi, Yu Ran; Joo, Moon-IL; Kim, Hee-Cheol
【Source】2021 23RD INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT 2021): ON-LINE SECURITY IN PANDEMIC ERA
【Abstract】For decades artificial intelligence (AI) has been used for various applications in the healthcare industry. Machine learning and artificial intelligence algorithms allow us to diagnose and customize medical care and follow-up plans to get better results, and during the covid19 pandemic, it was found that AI models have been using to predict the Covid-19 symptoms, understanding how it spreads, speeding up research and treatment using medical data. However, it is very challenging to make a robust AI model and use it in a real-time and real-world environment since most organizations do not want to share their data with other third parties due to privacy concerns, furthermore, it is difficult to build a generalized prediction model because of the fragmented nature of the patient data across the healthcare system. To solve the above problems, this paper presents a solution based on blockchain and AI technologies. The blockchain will securely protect the data access and AI-based federated learning for building a robust model for global and real-time usage.
【Keywords】Artificial intelligence; blockchain; federated learning; privacy; pandemic
【摘要】几十年来，人工智能 (AI) 已被用于医疗保健行业的各种应用。机器学习和人工智能算法使我们能够诊断和定制医疗护理和后续计划以获得更好的结果，并且在 covid19 大流行期间，发现 AI 模型一直用于预测 Covid-19 症状，了解它是如何传播，使用医学数据加速研究和治疗。然而，由于大多数组织出于隐私问题不想与其他第三方共享数据，因此制作一个强大的 AI 模型并在实时和真实的环境中使用它是非常具有挑战性的，而且很难由于整个医疗保健系统中患者数据的分散性，因此建立了一个通用的预测模型。针对上述问题，本文提出了基于区块链和人工智能技术的解决方案。区块链将安全地保护数据访问和基于 AI 的联邦学习，以建立一个可靠的全球实时使用模型。
【关键词】人工智能;区块链；联邦学习；隐私;大流行
评论