智慧醫療的新時代：從大數據到精準醫療

A new era of Smart Medicine: From big data to Precision Medicine

隨著全球人口老化和醫療需求增加，傳統醫療模式已無法應對現代需求，智慧醫療因而成為醫療發展的核心之一。智慧醫療整合大數據、人工智慧、物聯網等技術，提升診斷精準度、治療效率與健康管理能力。透過大數據分析，醫療人員可處理多樣化來源的資訊，如電子病歷、多體學資料、穿戴裝置資料及醫學影像，以支持精準醫療與預防保健。人工智慧技術則在疾病風險評估、影像識別及個案管理上展現卓越表現，並助力自動化病歷生成與臨床決策支持系統的發展。此外，穿戴式裝置與遠距監測技術讓日常健康資料收集與分析變得便捷，特別在慢性病管理與「在宅住院」模式中有很好的應用。然而，智慧醫療的發展面臨資料標準化、隱私安全及人工智慧模型透明度等挑戰。未來需加強資料整合技術與隱私保護措施，並促進人工智慧模型的可解釋性，才能充分發揮智慧醫療的潛力，實現高效、個人化的健康照護目標。

With the aging global population and increasing healthcare demands, traditional medical models are insufficient to meet modern needs. As a result, smart healthcare has become a core focus in healthcare development. Smart medicine integrates technologies such as big data, artificial intelligence (AI), and the Internet of Things (IoT) to enhance diagnostic accuracy, treatment efficiency, and health management capabilities. Through big data analytics, healthcare professionals can process diverse sources of information, including electronic health records (EHRs), multi-omic data, wearable device data, and medical imaging, to support precision medicine and preventive care. AI has demonstrated exceptional performance in disease risk assessment, image recognition, and case management, while also contributing to advancements in automated medical record generation and clinical decision support systems (CDSS). Furthermore, wearable devices and remote monitoring technologies facilitate the seamless collection and analysis of daily health data, proving particularly useful in chronic disease management and the“hospital-at-home”care model. However, the development of smart healthcare faces challenges such as data standardization, privacy security, and the transparency of AI models. To fully realize the potential of smart healthcare and achieve the goals of efficient and personalized health care, future efforts must focus on enhancing data integration technologies, strengthening privacy protection measures, and promoting the interpretability of AI models.