healthcare ai

Edward Reiner’s career maps the three-decade arc of healthcare’s data revolution: from paper records to enterprise data warehouses to the arrival of large language models and generative AI tools that promise to reshape clinical workflows, drug development, and health-system management. His...

As the first quarter of 2026 unfolds, the era of AI experimentation in the enterprise has given way to an era of accountability. After three years of pilots, proofs of concept, and vendor sampling, buyers are consolidating their stacks, procurement teams are pruning experiments that never...

MIT Technology Review’s new short series, Making AI Work, lands as a practical counterpoint to the hype: a seven-issue, weekly newsletter that walks readers from real-world case studies to the tooling and — critically — the operational steps organizations need to make AI deliver measurable...

CU Anschutz researchers are moving from proof‑of‑concept to practical deployment, delivering a set of validated, clinician‑centered tools designed to make Large Language Models (LLMs) and other health A.I. safer, auditable and useful at the bedside—efforts that combine peer‑reviewed measurement...