AI Engine to Maximize Commercial Reach | Finding Invisible Patients with AI

Millions of patients remain invisible to the healthcare system — undiagnosed, misdiagnosed, or never reaching the right treatment. In this session, Shihan He, Machine Learning Engineer at Novo Nordisk, explores how AI can bridge the gap between clinical innovation and real-world patient access by combining predictive machine learning with generative AI. The talk introduces a dual-module approach: using real-world data to identify high-probability patient signals, then turning those insights into personalised, actionable engagement for healthcare teams. ⏱️ Key moments: 00:00 The invisible patient problem 01:21 Why commercial excellence matters in life sciences 03:20 Why traditional go-to-market models are breaking 06:22 Agentic AI for commercial operations 08:02 Using real-world data to identify patient signals 08:33 From predictive models to personalised engagement 12:23 Scaling AI with governance and observability 15:23 Turning raw data into patient impact 📌 Applied Healthcare AI Summit 2026 — real-world AI deployment in healthcare, from pilots to production systems. #HealthcareAI #AIinHealthcare #PatientAccess #RealWorldData #DigitalHealth #LLM