Liu, YiyaoYiyaoLiuWu, YaYaWuRen, Hong-XiaHong-XiaRenWu, ShaoquanShaoquanWuHong, JialeJialeHongDu, JiaJiaDuSun, MingyanMingyanSunZONG-HONG LINMiao, Yang-BaoYang-BaoMiao2025-11-142025-11-142025-12-0122112855https://www.scopus.com/record/display.uri?eid=2-s2.0-105017116223&origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/733683The spatiotemporal dynamics of diseases are fundamental to understanding their progression, transmission, and treatment efficacy. Integrating wearable devices with artificial intelligence (AI) provides unprecedented capabilities for capturing real-time physiological and behavioral data, enabling a comprehensive exploration of disease patterns across time and space. This review examines the evolution of diseases through a spatiotemporal lens, highlighting how AI-driven wearable technologies revolutionize health monitoring, disease characterization, and therapeutic strategies. It systematically introduces the design and development of AI-integrated wearable devices and categorizes diseases to elucidate how this synergy transcends conventional diagnostic and treatment paradigms. Furthermore, the latest advancements in clinical applications, existing challenges, and potential solutions are discussed. By leveraging AI-enhanced wearables, this integration not only refines disease monitoring and analysis but also unlocks new frontiers in personalized healthcare, ultimately shaping the future of precision disease management.falseArtificial intelligenceDynamicsHealth monitoringPrecision medicineSpatiotemporal diseaseWearable technologyjournal article10.1016/j.nanoen.2025.1114812-s2.0-105017116223