作为聚焦前沿交叉研究的学术团队，Miracle为学界同不一则重磅征稿信息—npj Digital Medicine（IF: 15.1）“AI for Population Medicine and Public Health”专刊正式开启征稿，领域内有相关成果的课题组、研究者千万别错过。

此次专刊由三位领域权威学者共同担任客座编辑，学术背书十足：

中国科学技术大学周少华教授（Miracle实验室PI）

中国医学科学院杨维中教授

昆士兰大学Amalie Dyda教授

投稿关键信息：

投稿网址：https://www.nature.com/collections/jaibcfdhef/how-to-submit

投递方式：通过上述链接直接投稿至npj Digital Medicine，投稿时需注明专刊

截稿时间：2026年5月

接收主题：

1. Early detection and warning of infectious diseases using multi-source data or multi-center medical big data or non-traditional data

2. Detection and tracing of pathogens, utilizing advanced algorithms to identify microbial threats and map their transmission pathways

3. Antibiotic resistance and usage pattern analysis, including pan-drug-resistant (PDR), extensively drug-resistant (XDR), and multidrug-resistant (MDR) detection, and population-level antibiotic utilization surveillance

4. Artificial intelligence-driven simulation and optimization of public health policies for enhanced decision-making and outcomes

5. AI-driven dynamic risk stratification for enhanced management of chronic diseases

6. Leveraging artificial intelligence algorithms to continuously assess and categorize the evolving risk levels associated with chronic conditions

7. Interaction and association between acute infectious diseases and chronic diseases based on big data

8. Advanced methods leveraging artificial intelligence to enhance clinical pathway optimization and streamline resource allocation in healthcare systems.

9. AI for wearable devices such as fitness trackers, smart watches, and biosensor patches

10. Multimodal fusion to effectively utilize the complementary characteristics of multiple data streams that are common in population medicine and public health

11. Translational use of edge computing in resource-constrained environments

12. Federated learning and privacy preserving to mitigate the data silo challenges that affect health practice

13. Foundational models designed for, and demonstrated on, downstream tasks in population medicine and public health

无论是深耕AI医疗算法研发，还是聚焦公共卫生实践转化，只要研究方向契合，都欢迎积极投递，期待更多优质成果在这一高水平平台发声，推动AI技术为人群健康事业赋能。