You’re carrying your health care early warning system is in your pocket

Your devices and AI are spotting risks to your health before they turn serious

Artificial intelligence is often talked about as something just around the corner in health care. But what if a device you already own could help spot a health problem early enough to make a difference?

The reality is that AI is already here, influencing how we monitor, organize and understand our own health data—even while parts of the system still feel stuck in another era.

I was reminded of that in a recent conversation with Dr. Earl Campazzi, a medical practitioner with more than 35 years of clinical experience. He pointed out that some AI systems already outperform humans in narrow tasks such as analyzing certain lab results. Yet patients are still routinely told to bring handwritten lists of medications to appointments or emergency rooms.

Campazzi’s book, Better Health with AI: Your Roadmap to Results, addresses that gap between advanced algorithms and handwritten lists. It is aimed squarely at everyday people. It doesn’t assume technical expertise, and it doesn’t suggest that algorithms should replace doctors. Instead, it explains how artificial intelligence, wearables and digital tools can help people organize information, recognize trends and make more informed health decisions. The book includes extensive references and reviews more than 80 health-related apps, focusing on practical use rather than hype.

Listen to the interview

One of the biggest misconceptions, Campazzi told me, is the idea that AI replaces human judgment.

“AI is very good at identifying trends over time,” he said. While it doesn’t replace doctors, it helps identify patterns they might otherwise miss.

The phone in your pocket or the watch on your wrist already collects information about heart rate, sleep, movement and stress every day. Most people glance at those numbers and move on. Fewer realize that, over weeks or months, they can reveal patterns that shouldn’t be ignored.

On any given day, a slightly elevated heart rate or a shorter night’s sleep may not seem significant. But over time, consistent shifts in those readings can point to changes in overall health—changes that are difficult for the human eye to detect without analytical help. That is the distinction Campazzi is making.

Campazzi shared examples of wearable data flagging irregular heart rhythms, including atrial fibrillation, a common heart rhythm disorder that increases the risk of stroke, before symptoms were obvious. In one case, a smartwatch detected an irregular rhythm before the wearer noticed anything unusual, prompting a doctor’s visit that reduced her risk of stroke. It gave her a head start.

He also described how AI tools helped a caregiver facing a cancer diagnosis organize complex information and prepare more focused questions for medical appointments, making the conversation more productive.

At the same time, Campazzi cautioned against obsessing over a single reading. We are prone to what psychologists call recency bias—putting too much weight on the latest number and assuming it tells the whole story. Looking at aggregated data provides a far more reliable picture than reacting to yesterday’s result.

That’s where AI makes the difference.

“There’s a lot of data in your wearables, your smartwatch, your phone, but on its own it doesn’t mean much,” Campazzi said. “When you download it and let AI look at it, suddenly you start seeing patterns. How sleep affects exercise. How poor sleep changes what you eat. That’s where the insight really starts.”

What struck me is that his message isn’t about complexity. Many smartphones already collect basic health data automatically, and a simple fitness tracker is often enough. Consistency matters more than sophistication.

One practical step he suggests is entering current medications, supplements and vitamins into an AI-assisted tool to check for potential conflicts.

“Many people don’t realize that some supplements don’t work well with certain medications,” he said.

Having that information organized in advance can make medical appointments more productive. In a health system where specialist referrals and diagnostic tests can take weeks or months, arriving prepared matters. Patients can clearly outline symptoms, medication lists and concerns—either in writing or verbally—so physicians spend less time gathering background details and more time discussing next steps.

Tools that demand heavy manual input tend to be abandoned, no matter how powerful they are. Campazzi notes that consistency usually matters more than perfect precision.

Take nutrition tracking. Detailed logging works in theory, but many people struggle to keep it up. Campazzi points to apps such as Foodvisor, which allow users to photograph meals instead of weighing and logging everything manually. The lower barrier increases the odds that users will stick with it long enough to see meaningful patterns.

Of course, not everyone wants to turn daily life into a stream of data. Campazzi stresses that the goal is perspective, not obsession. Not every fluctuation signals a problem. Noticing when something changes is what matters.

For all the talk of digital health, he also stresses some decidedly low-tech advice. Keep a printed list of medications, dosages, supplements, allergies and major medical conditions in a wallet or purse.

“In an emergency, paper still works,” he said.

Privacy is another practical consideration. Campazzi suggests limiting unnecessary personal identifiers, using common sense when sharing information and remembering that most health data is generally less attractive to bad actors than financial data.

Importantly, his book frames AI as a support tool—something that helps patients organize information, notice trends and ask better questions when they sit down with their health-care providers.

Some still view AI in health care as futuristic or even science fiction. Campazzi sees it differently. AI-powered analysis of wearable data, medication tracking tools and health apps are already being used in targeted ways, even if adoption varies. Expectations should remain realistic. But paying attention earlier often changes what happens later—and the tools to do that are already in our hands.

Greg Gazin, also known as Gadget Guy or Gadget Greg, is a Troy Media columnist with deep expertise in technology. He’s also a respected speaker on communication, leadership, and tech-related topics. Beyond writing, Gazin is a versatile professional who works as a facilitator, blogger, podcaster, and author. His broad range of skills and insights has made him a prominent and influential voice in the tech community.