1. Early Detection of Sepsis – Support for Nurses 🏥 Location: Johns Hopkins Hospital, USA 🛠️ Tool: AI-Powered EHR Sepsis Alert System Nurses were equipped with real-time alerts embedded in the EHR to detect early signs of sepsis based on vitals, labs, and clinical notes. The AI system prompted bedside nurses to escalate care when critical thresholds were met. ✅ Outcome: - Reduced sepsis-related mortality by 20% - Enabled nurses to escalate care more confidently and promptly 💡 Key Insight: AI enhanced early recognition and nurse-led interventions, especially in busy wards.

2. Risk Prediction in Chronic Disease – General Practice 🏥 Location: UK NHS Primary Care 🛠️ Tool: QCovid AI Risk Calculator GPs used the QCovid model to assess patients’ risk of severe outcomes from COVID-19, considering age, sex, ethnicity, and comorbidities. This helped guide patient prioritization for shielding, vaccination, and remote monitoring. ✅ Outcome: - Enhanced risk stratification and personalised care - Supported decision-making during uncertain clinical scenarios 💡 Key Insight: AI helped GPs deliver proactive, risk-informed care to vulnerable populations.

3. AI-Guided Rehabilitation – Allied Health 🏥 Location: Singapore General Hospital 🛠️ Tool: AI Motion Tracking & Feedback System Physiotherapists used AI motion sensors during stroke rehabilitation to analyze movement patterns and provide real-time feedback on exercises. The system tracked progress and adjusted difficulty levels. ✅ Outcome: - Improved patient engagement and adherence - Enabled remote monitoring and reduced in-person visits 💡 Key Insight: AI tools empowered allied health professionals to extend care beyond the clinic and personalise recovery plans.