声明:本文来自于（ID:7maime.com）授权转载发布。

党的二十届三中全会通过的《中共中央关于进一步全面深化改革 推进中国式现代化的决定》(下称《决定》)提出，深化医药卫生体制改革，促进优质医疗资源扩容下沉和区域均衡布局，强化基层医疗卫生服务。《决定》还提出，部署完善生成式人工智能发展和管理机制、建立人工智能安全监管制度等。

相关话题，是意大利特伦托大学信息工程与计算机科学系教授福斯托·金奇利亚(Fausto Giunchiglia)的关注重点之一。他希望深入了解，中国将如何促进医疗资源分配及推动城市规划，助力高质量发展。

在中新网《问答中国》栏目中，北京理工大学管理学院副研究员尹西明对金奇利亚的提问，作出解答。他表示，人工智能作为一种先进技术，可以大幅降低很多疾病的预诊断成本以及看病成本。此外，该技术还可以实现从看病到报销一体化，提升基层在医疗资源分配上和医疗效率上的问题。他指出，在智慧城市和交通规划发展方面，人工智能将大有可为。(薛凌桥 陈天浩)

The resolution adopted by the 20th Central Committee of the Communist Party of China on further deepening reform comprehensively to advance Chinese modernization at its third plenary session has said that China will further reform the medical and healthcare systems. It requires the country do more to increase the availability of quality medical resources and ensure that such resources are channeled toward the community level and more evenly distributed among regions. The resolution also emphasized the importance of Artificial Intelligence (AI), noting that China will improve the mechanisms for developing and managing generative artificial intelligence, as well as strengthening the institutional oversight systems to ensure the safety of AI.

As a professor at University of Trento, Department of Information Engineering and Computer Science, Fausto Giunchiglia pays close attentions to the session. Raising questions on China’s high-quality development, he hopes to understand how will the country promotes the allocation of medical resources and advance urban planning.

In response to the questions, Yin Ximing, associate researcher at the School of Management in Beijing Institute of Technology, said that as an advanced technology, AI will substantially reduce cost of disease prediagnosis and medical treatment at many levels. AI will also enabled  one-stop service for medical treatment and reimbursement, thereby greatly improving the medical resources allocation and treatment efficiency at primary level. He also pointed out that AI will have many applications on the building smart cities and transportation planning. (Xue Lingqiao and Chen Tianhao)