[From Sensing to Decision: Leveraging Technology to Enhance Nursing Clinical Judgment]

With the rapid integration of Artificial Intelligence (AI), the Internet of Things, and sensing technologies into healthcare, the nursing frontline is undergoing a structural transformation from "sensory-driven" to "data-driven" practice. Tools such as wearable sensors, generative AI, and remote monitoring systems enable the real-time and continuous acquisition of physiological data. However, the increase in data volume does not inherently equate to improved clinical judgment. When excessive alerts and information infiltrate the workflow, these data may trigger cognitive overload and alarm fatigue. In this article, the "Sensing-Integration-Decision" framework is adopted to explore how sensing technologies expand the clinical observation capabilities of nurses and how clinical decision support systems facilitate the conversion of fragmented data into actionable care insights. Also, the essential competencies required of nurses in tech-assisted environments, including data literacy, clinical integration skills, and the core spirit of humanistic care, are explored. Furthermore, ethical issues arising from technology-mediated care such as data privacy, algorithmic bias, and the risk of over-reliance, are addressed. Finally, concrete recommendations for nursing education and practice are provided to guide professional development in the era of smart healthcare.