By the end of this workshop, participants will be able to:
1. Explain how artificial intelligence (AI) supports clinical decision-making in nursing, including risk detection, patient triage, and early prediction of health deterioration.
2. Identify examples of Al applications in patient monitoring, such as vital sign tracking, mood or pain assessment, and data collection through wearable sensors.
3. Interpret predictive analytics outputs that inform nursing judgments, including risk for readmission, falls, infection, or adverse events.
4. Discuss ethical considerations, potential bias, data privacy, and implications for professional accountability in the use of Al tools in nursing practice.
6 November, 2025
Learning Objectives
By the end of this workshop, participants will be able to:
1. Explain the concept of innovation and its significance in advancing nursing practice and research.
2. Identify current challenges in healthcare delivery that can be addressed through innovative approaches.
3. Apply creative and evidence-based strategies to improve patient care and research outcomes. 4.Collaborate effectively with interdisciplinary teams to promote a culture of innovation and continuous improvement in nursing.
5 November, 2025
