Perspectives on clinical AI
Honest writing on healthcare data, grounded AI and what it takes to make clinical AI useful.
Why AI Stalls in the Healthcare Enterprise
Most healthcare organizations have moved past the question of whether to adopt AI. The question now is why the investment keeps falling short of the return — and what's getting in the way.
Healthcare Data Is the Crude Oil. We’re Finally Building the Refinery.
The raw material has been sitting there for decades — in EHRs, in notes, in labs, in devices nobody fully reads. What’s changing now is our ability to process it.
Data Liquidity Is Not a Feature. It’s the Precondition for Everything Else.
Most healthcare data platforms solve for completeness. That’s the right first problem. But there’s a harder one behind it: whether the data can get to where it’s needed, in the shape…
Building Healthcare AI You Can Trust
Why the Harness — Not the Model — Turns “it might work” into “you can count on it”
AI Agents Are Coming to Every Corner of Your Practice. Most of Them Are Going to Disappoint You.
The front office, the exam room, the billing department — agents are being built for all three. Here’s what they can realistically do today, where they break, and why they all depend on…
The AI Found the Signal. Now It Has to Do Something With It.
Retrieval gives the AI your patient’s chart. Investigation surfaces what matters. Synthesis turns findings into decisions — and that’s where most clinical AI stops short.
Clinical AI that knows everything about medicine and nothing about your patient isn’t clinical AI. It's search. Here’s what changes when that gap closes.
Most clinical AI tools know everything about medicine and nothing about your patient. A landmark enterprise deployment just proved what changes when that gap closes — and why it matters…
Smart Isn’t the Same as Useful.
What the AI Vendors Aren’t Telling You About Why Their Demos Look Better Than Their Products.
Find It. Do It. Write It.
Forget the Hype. These Are the Three Things AI Can Actually Do in Healthcare Right Now.
The Invisible Infrastructure: Why Ontologies Determine Whether Your Healthcare AI Actually Works
FHIR gives you the shape of healthcare data. Ontologies give it meaning. Without both, your AI is guessing.
Built for Nobody
Why the most sophisticated healthcare AI means nothing if real people can’t use it — and whose fault that actually is.
We Digitized Healthcare. We Just Didn’t Make It Any Better.
How the technology that was supposed to fix American healthcare became part of the problem
Why America Spends 50% More on Healthcare—And Gets Worse Results.
The uncomfortable truth about where our healthcare dollars actually go
We’re done with the noise. Here’s what we’re building instead.
”Honest conversations, real perspectives, and zero hype about how AI and healthcare are reshaping each other.”
Why ROI for GenAI is hard: Part 2
In the last blog, we focused our attention on why it is easy to overestimate the benefit of GenAI solutions. In this blog, we will focus on why it is easy to underestimate effort and…
Why ROI for GenAI is Hard: Part 1
Over the last few articles on this blog, we have mainly focused on why raw pieces of GenAI technology, may it be just LLM models or frameworks like RAG, may not be sufficient for solving…
In Fact, Retrieval Augmented Generation Is Also Not Enough to Meet User Requirements in Healthcare.
In the previous blog, we discussed how LLMs by themselves are insufficient for satisfying user requirements in healthcare. We suggested, at the minimum, we needed frameworks like RAG to…
LLMs Alone are not Enough to Satisfy user Requirements in Healthcare
In the previous blog, we discussed user requirements for Generative Artificial Intelligence (Gen AI) solutions to work in healthcare. We proposed that we not only need the application…
What is Needed to Make GenAI Work for Users in Healthcare?
As discussed in the previous blog, administrative processes in healthcare may be a high-value target for impact by artificial intelligence (AI). However, many technical challenges…
What is Missing From Healthcare AI Efforts? User Centricity
At ThetaRho, we strive to provide a non-obvious but informed perspective on the challenges and opportunities for AI in healthcare. We believe that the end-user perspective is…
A Day in the Life of a Physician
All day long, physicians perform critical cognitive activities such as assessing an individual’s risk of developing a medical condition, diagnosing the probable disease underlying a…
What can Beat Artificial Intelligence? Natural Stupidity
The events of the weekend of November 17 2023, will take time to be understood by history. The dramatic firing of OpenAI’s CEO Sam Altman and President Greg Brockman, followed by their…
Meet our New Chief Medical Officer, Dr. Shyam Visweswaran MD, PhD
ThetaRho welcomes Shyam Visweswaran MD, PhD as Chief Medical Officer. With degrees in both medicine and artificial intelligence, Dr. Visweswaran is at the forefront of a select group of…
Are Clinicians Really Burning Out From Poor EHR Usability?
In the previous blog article, we encountered physician burnout as a burning topic in healthcare. In this article, we explore the problem to understand what role technology can play in…
Theory vs Practice
A lot of ink has been spilt over the last 10+ years on the potential impact AI will have in healthcare. In fact, it has been over a decade since it was reported that a prominent venture…
You own your healthcare data.
You should be able to use it as you like, with AI you trust. Let's start the discussion.