John Snow Labs 58d ago

Healthcare AI doesn’t fail at the model — it fails at the last mile. This session breaks down why even high-performing LLMs don’t translate into real clinical impact — and what actually determines whether AI is trusted and used in practice. ⏱️ Key moments: 00:00 Why better models don’t guarantee better outcomes 02:20 The “last mile” problem in healthcare AI 05:00 Where LLM outputs fail in practice 08:10 Accountability: who owns AI-generated content 11:20 Building trust: rigor, validation, and human judgment Núria Negrão (Medical Writer & AI Adoption Strategist) explains why the biggest risk in healthcare AI is not generation quality, but human curation, accountability, and workflow design. Most teams focus on improving models. In reality, failure happens when outputs reach clinicians — where accuracy, evidence, and responsibility must hold under real-world pressure. This talk introduces the “last mile” problem in healthcare AI: how human-in-the-loop systems, governance, and content validation determine whether AI creates value — or risk. Original session: “The Last Mile of Healthcare AI: Why Your LLM Is Only as Good as the Humans Curating Its Output” 📌 Applied Healthcare AI Summit 2026 — real-world healthcare AI, from pilots to production systems. #ClinicalAI #MedicalAI #HealthcareAI #AIinHealthcare #AIGovernance #LLM #HumanInTheLoop #AIAdoption #ClinicalWorkflows #HealthTech #AIinProduction #ResponsibleAI