Healthcare AI Is Mainly Bullshit

If it comes from a black box, would you bet your license on it?

If you’ve been paying attention, you know that AI is the hottest thing in healthcare right now. Every company, every venture capital fund, every health system is scrambling to position themselves as “AI-powered,” promising revolutionary breakthroughs in diagnosis, treatment, and patient care.

But let’s cut through the noise: most healthcare AI is completely useless.

Why? Because AI is only as good as the data it’s built on. And right now, the data is garbage.

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The Problem With AI in Healthcare

Take cognitive decline as an example. There have been hundreds of studies on Alzheimer’s and dementia over the past few decades. AI could theoretically process all of them, pulling insights from every research paper, clinical trial, and meta-analysis ever written.

Sounds great, right? Except for one small problem:

The dominant hypothesis of cognitive decline—the beta-amyloid hypothesis—was built on fraudulent research.

For 20+ years, billions of dollars have been poured into drug trials targeting beta-amyloid plaques in the brain, based on a theory that these plaques cause Alzheimer’s. But not only have these treatments failed spectacularly at reversing cognitive decline, recent investigations have revealed that the entire premise may have been based on manipulated research.

So, if AI scans thousands of studies based on a failed paradigm, what good does that do? All you’re doing is training a machine to make better predictions based on bad science.

AI can only “think” within the constraints of the dataset it’s trained on. Garbage in, garbage out.

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What AI Should Be Built On

If we want real AI-powered healthcare solutions, we need a radically different kind of database—one that actually tracks what works in real-world clinical settings.

Here’s what that AI-powered system would look like:

1. Outcomes-Driven Data (Not Drug Trials)

• Instead of basing AI on theories and drug research, we track real outcomes from functional and precision medicine clinics.

• Wearables + lab data + cognitive function tests = objective results, not subjective interpretations.

2. Tracking What Patients Actually Do

• AI should not just analyze clinical notes. It should track what the patient was actually told to do—and what they actually did.

• Did they take their supplements? Did they exercise? Did they improve their sleep?

• Right now, AI has no way of knowing whether a patient ignored their doctor’s advice or followed it exactly—and that’s a massive blind spot.

3. Multi-Dimensional Tracking of Health Inputs

• Cognitive decline (and most chronic diseases) are driven by multiple factors:

  • Metabolic health

  • Inflammation

  • Gut-brain axis

  • Toxin load

  • Psychosocial & environmental factors

• AI must analyze ALL of these inputs to understand what truly reverses disease.

For example:

• What has a bigger impact on reversing cognitive decline—eating a pound of blueberries every day or making a new friend?

• Is a daily 20-minute walk more effective than optimizing Omega-3 levels?

• Which combination of interventions is the most cost-effective and scalable?

We don’t know the answers to these questions because no one is tracking the data in a structured, meaningful way.

But we could know—very quickly—if we structured the database correctly.

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The TruNeura Approach: Building the Right Database for AI

At TruNeura, we’re not here to blindly follow the AI hype cycle. We’re here to build the right foundation so that when AI does take over healthcare decision-making, it actually improves patient outcomes.

Here’s how we’re doing it:

1. Standardizing Inputs

• We are deploying our baseline precision medicine protocols across clinics using TruNeura’s software. Each tenant will be able create their own protocols and choose to share them with the entire network if they wish.

• This means every clinic is tracking the same structured inputs and outcomes—allowing for true AI-driven insights over time.

2. Closing the Loop on Patient Actions

• Instead of just tracking lab results, TruNeura tracks what patients actually do.

• Are they following their protocols? Are they exercising? Sleeping?

• With real-time patient-reported data and wearable integration, we get a full picture of health inputs—not just isolated lab values.

3. Aggregating Wearable, Lab, and Behavioral Data

• AI is most powerful when it analyzes multiple data streams together.

• TruNeura integrates wearables (HRV, sleep, movement), lab results, environmental exposures, and psychosocial factors into one unified dataset.

This creates a feedback loop where we can see:

• What interventions drive the biggest improvements?

• Which ones are not worth the time and money?

• What’s the most efficient, affordable way to reverse cognitive decline

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Why This Matters Now

AI is improving on its own, regardless of what we do. The algorithms will get better, faster, and smarter. But if the underlying data is wrong, AI will only accelerate bad medicine.

By the time next-generation AI reasoning models come online, we will have built the dataset they should be analyzing.

That means instead of AI telling us which failed Alzheimer’s drug to try next, it will be telling us:

• The exact combination of lifestyle changes, supplements, and therapies that work best for the individual phenotype in front of you.

• How to personalize cognitive decline protocols to individual patients.

• How to scale these interventions to millions of people.

This is the future of AI in medicine—not reading bad research, but analyzing real-world outcomes.

And this is exactly what we’re building at TruNeura.

The Bottom Line

If you’re a doctor, clinic owner, or precision medicine practitioner, the next five years will redefine how you practice. AI is coming—but whether it helps or hurts depends entirely on the data it has to work with.

At TruNeura, we’re ensuring that the data feeding into future AI models is built on real-world, outcomes-driven, root-cause medicine—not flawed pharmaceutical research.

If you want to be part of this revolution—if you want to be on the right side of AI-driven healthcare—it starts with tracking the right data, right now.

Because when the next wave of AI-powered healthcare arrives, you’re either riding it—or being replaced by it.

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Want to be ahead of the curve?
Join the TruNeura network and start building the future of cognitive health today.