A calf cramp should not be a brush with death. Mine almost was.
For more than two weeks, I had what felt like a stubborn muscle spasm in my left calf. It was tender, swollen and getting worse. I assumed it was a muscle problem and went to my chiropractor, who treated it as a muscle issue.
But the pain kept worsening, and I turned to an AI health tool I had built for myself, based on my expertise training companies on how to adopt AI tools effectively, using my medical records, medications, lab work, and visit notes. It flagged deep vein thrombosis, or DVT, and pointed me to the diagnostic step that mattered: an ultrasound.
DVT is a blood clot in a deep vein, usually in the leg. Symptoms can include pain, swelling, warmth, and skin colour changes, especially when they affect one leg. Clinical guidelines also say suspected DVT should be assessed urgently and, when a doctor thinks DVT is possible, the patient should be referred quickly for an ultrasound scan.
So I called my primary care office, which advised me to schedule an appointment or go to urgent care.
Ordinarily, that would have sounded sensible. But urgent care, a step below an emergency room run in the U.S., could not provide the scan. My doctor’s office could not provide it either. If I followed the slow path, I might lose several days before being sent to the emergency room anyway.
AI didn’t cure me, but helped me ask the right question
That question mattered because deep vein thrombosis can be fatal when part of a clot breaks off and travels to the lungs, causing a pulmonary embolism. The CDC classifies both conditions as serious conditions that are often underdiagnosed.
So I decided to listen to my AI tool, and headed to a local ER.
A few hours later, an ultrasound found four clots in my left leg.
Afterward, the danger stopped being theoretical. I learned that my wife’s grandfather died from a pulmonary embolism. So did the mother of one of her close friends. What had felt like a nagging cramp suddenly looked like the edge of a cliff.
This is not an argument for replacing doctors with machines.
The emergency room doctors did the indispensable work. They ordered imaging, interpreted results, weighed whether to admit me, spoke with specialists and sent me home on blood thinners when it was safe to do so. The AI did not cure me.
But it did help me ask the right question in time. And science is catching up with these stories.
A new study on medical AI in Science, led by Harvard Medical School and Beth Israel Deaconess Medical Center researchers, tested a large language model on clinical reasoning tasks, including real ER. Science News reported that the model was more likely than physicians to include the correct diagnosis among possible answers.
There is also a danger of relying too much on AI
That does not mean patients should trust random chatbots over clinicians. It means doctors and AI may be safer together than either is alone.
A useful AI system can surface possibilities, organize medical records, help patients describe symptoms clearly and reduce the chance that a dangerous pattern gets mistaken for something ordinary.
There is also real growing danger of relying too much on AI.
A Guardian report on AI health advice found that one in seven people in the U.K. are using AI chatbots for medical guidance instead of seeing a doctor. That should worry everyone. A chatbot cannot examine a leg, hear breathlessness, notice distress or take responsibility for a patient.
But fear should not become denial. AI in health care needs regulation, testing, transparency and clinical supervision. It also needs humility from institutions that too often expect patients to navigate fragmented systems alone.
My lesson is not that everyone should outsource their health to software. It is that patient advocacy now has a new tool. A safe AI assistant, trained on your medical data, can help people gather their records, ask whether something urgent is being missed and push for the right diagnostic step.
Medicine has always depended on second opinions.
The next one may come from software, and the urgent task is to make sure it is accurate, accountable and used to save lives.
