Author's posts
Model context protocol: the standard that brings AI into clinical workflow
The real limitation of clinical AI isn’t the model; it’s the context. AI can draft notes, flag interactions, and read scans. However, when it comes to understanding the patient in front of you, it’s still a matter of working in the da…
“Think twice, heal once”: Why medical decision-making needs a second opinion from your slower brain (and AI)
Medicine demands fast decisions. Chest pain in triage. A vague complaint from an elderly patient. A scan with subtle shadows. But the speed that saves lives can also lead to predictable, systematic errors, especially when we trust our gut too much. Psy…
AI agents in health care: Balancing innovation, trust, and evidence-based implementation
Artificial intelligence (AI) agents significantly transform health care by automating routine tasks, enhancing clinical decision-making, and reducing administrative burdens. These intelligent systems are increasingly applied in medical documentation, d…
Small language models and edge technology: Transforming health care delivery
Artificial intelligence (AI) advances are ushering in a new era of health care innovation, and small language models (SLMs) deployed on edge devices are leading the charge. Unlike large-scale AI systems, SLMs are lightweight, efficient, and capable of …
How each generation sees AI: a reflection on adaptation
Disclaimer: This is a broad generalization meant to spark reflection. While no one perfectly fits into generational boxes, these insights are designed to explore how each age group navigates the evolving world of artificial intelligence (AI). Generatio…
