Radiology AI’s CAD Déjà Vu: Lessons for Investors
The hype around diagnostic AI is deafening, but for anyone who’s been around long enough, it feels a lot like déjà vu. The way modern…
AI’s Hidden Flaw: Why Shortcut Learning Threatens Cardiac Diagnostics
The hype around AI in healthcare, especially for diagnostic imaging, is all about boosting efficiency and accuracy. But there’s a critical vulnerability hiding behind impressive…
AI Pathology: Navigating Safety & Oversight for Investors
There’s no question AI is going to change diagnostic pathology, especially by making cancer detection faster. But as venture capitalists look at all the new…
Stop the Bleed: Auditing AI Drift in Cardiac Care
AI in healthcare promises a lot, but that value disappears fast if you ignore algorithmic drift. Clinical environments are constantly changing, patient populations shift, new…
Sepsis AI: High False Positives, High Costs. Is the ROI There?
Automated sepsis alerts look like a critical lifeline on paper, promising to spot deadly infections faster than any human can. The reality of deploying these…
Cardiac AI: Benchmarking Automated ECG Against Clinical Gold Standards
Investors see the obvious appeal of remote patient monitoring (RPM) in cardiology: a massive total addressable market (TAM) thanks to chronic disease and the promise…
Why LLMs Fail Clinical Validity in ED Triage: A VC De-Risking Guide
Generative AI in healthcare is getting a lot of attention for its potential to fix administrative headaches, and for good reason. But the jump from…
Algorithmic Drift: The Silent Threat to AI ROI in Radiology
The excitement around AI in diagnostic imaging is about speed and accuracy, and for good reason. But we’re deploying these tools with a dangerous blind…
Medicare’s AI RPM Shift: Winners, Losers, and Your Investment Strategy
The digital health gold rush in AI-driven remote patient monitoring (RPM) is over. For venture capitalists and digital health growth equity investors, the era of…
FDA’s AI Plan: De-Risking SaMD for Billion Dollar Returns
The old regulatory path for medical devices, designed for unchanging hardware and software, was always a terrible fit for machine learning. Any time you wanted…