Tagged: healthcare AI
6 articles on healthcare ai.
Healthcare AI Will Be Won by Verticals. The Recipe Has Been Around for a Decade.
Most healthcare AI companies are failing for the same reason. The ones winning are running the same playbook: one Palantir figured out before anyone called it AI. Forward-deployed engineer. Ontology. Integrations. Then AI tooling.
Vision + Language: How Multimodal LLMs Actually Work (And When to Use Them)
Multimodal LLMs integrate vision through two fundamentally different architectures. Knowing which one you need, and why, shapes every other technical choice in your build.
FHIR Meets Graph Databases: Exploring Healthcare's Natural Network Structure
FHIR data is a graph. Treating it as flat tables is why most healthcare AI struggles with relationships between patients, providers, and encounters. What happens when you model it the way it actually is.
The GenAI Strategy Question You're Not Asking (But Should Be)
Everyone asks 'how should we use GenAI?' The honest answer requires a harder question: does AI's unique capability create new value here, or is it just a more expensive way to do something that already worked? A practitioner's framework for getting this right in healthcare.
Inside the Black Box: What Mechanistic Interpretability Means for Builders
Healthcare AI requires explainability. 'The model said so' is not a clinical rationale. Mechanistic interpretability is the research field trying to change that. What it offers practitioners today, where the gap is, and what to do in the meantime.
How to Actually Test If Your AI Will Say Something Dangerous
Most teams treat jailbreak testing as a vibe check. StrongREJECT achieves 0.90 Spearman correlation with human judgment. Automated safety evaluation is real, and there's no excuse not to build it into your pipeline.