Clinical AI Governance: What Clinicians Must Know in 2026 скачать в хорошем качестве

Clinical AI Governance: What Clinicians Must Know in 2026

AI in healthcare is accelerating fast—but adoption without governance is risk. In this conversation, oncology and health policy leaders break down how clinicians and health systems should evaluate emerging AI tools: what FDA clearance vs approval really means, why “not FDA-approved” doesn’t automatically mean unsafe, and how laboratory-developed tests (LDTs) are already embedded in everyday care. We also explore real-world evidence, model drift, and why implementation—not innovation—is the true bottleneck for safe scale. If you’re assessing AI in imaging, diagnostics, clinical decision support, or workflow automation, this is your framework for asking smarter questions and protecting patients. Subscribe for conversations at the intersection of AI, cancer care, and clinical operations—and share this with your team building AI governance in 2026. - - -TimeStamps - - - - 00:00 Introduction 03:41 Understanding FDA Approvals for AI 05:21 The Role of Laboratory Developed Tests (LDTs) 10:04 AI in Clinical Decision Making 19:32 The Future of AI and Real-World Evidence 25:52 Concerns About AI in Healthcare 30:31 Challenges in AI Implementation 34:01 AI in Diagnostic Radiology 46:54 Future Predictions for AI in Healthcare #healthcare #aiinhealthcare #cancercare