Automation Bias: The Hidden Risk in Clinical AI Adoption
AI is supposed to help us work faster and be more accurate in the clinic, but there’s a catch. We’re all susceptible to “automation bias”,…
AI Health Claims: What VCs Must Ask Before Investing
AI in healthcare has a lot of potential, but getting it to work safely is a messy, complicated business. If you’re a buyer or a…
Sepsis AI: Why Early Promise Can Mislead Investors
The hype around AI in healthcare is that it can spot critical conditions like sepsis way earlier and better than we can now. But the…
Beyond AUC 0.86: Unmasking True Cardiac AI Performance
The idea that AI in healthcare will be some perfect, tireless system watching over patients is a common one. But getting a model from a…
Vendor vs. Independent AI: Unpacking Conflicting Cardiac Claims
When you’re trying to bring AI into a clinical workflow, you’re going to get hit with a firehose of vendor claims. The real challenge for…
IBM Watson’s MD Anderson Failure: A Data Infrastructure Lesson
Everyone’s talking about how AI will change healthcare, but getting it to work in a real hospital is a mess. We obsess over model accuracy,…
Clinical AI: Why Good Models Fail in the Real World
People talk about AI in healthcare as either a total revolution or a complete disaster, but that misses the point for the teams doing AI…
AI’s Data-Up Revolution: Reshaping Medicine’s Future
The article appears to be up-to-date as of September 20, 2026. All time-sensitive claims, including Ziad Obermeyer’s affiliations, publication dates, seminar dates, and recognition, remain…
AI in Healthcare: Promise, Peril, and Billions at Stake
The hype around AI in healthcare tends to drown out the real conversation we need to have about its complexities and real-world risks. If you…
Prenosis: The Sepsis AI That Dared to Seek FDA Clearance Early
A quick editor’s note: We’ve reviewed this piece as of September 21, 2026, and all the core facts are still solid. Specifically: The Sepsis ImmunoScore’s…