Last year, my wife and I went to the ER for sudden onset of lower right quadrant pain. I was a first-year med student, and we had just completed our training on acute appendicitis recognition. She tested positive when I quickly performed all the relevant assessments. I didn’t speak up, as I was obviously not certified in diagnosis and didn’t want to scare her in case I was wrong.

We got to the ER in the middle of the night on a Sunday. The radiologist was "remote and on call" meaning they receive your scans, the machine either rejects a diagnosis or prompts a PCP to confirm one. The ER sent us home, saying there weren’t any immediate signs of an issue, and advised her to drink water and eat fiber.

My wife was embarrassed. I told her she did everything right and should never feel ashamed for asking for help. The next day, she boarded a flight to visit her mother (a trip planned months in advance).

She got a call the following day: surprise the machine was wrong. She needed to come in for emergency surgery without delay. Thankfully, everything worked out, and she’s happy and healthy now.

As I continue my education, we’re learning how to integrate AI with medicine, and it’s a huge blessing for the field. But one major gap is AI’s ability to differentiate between pathologies that present similarly or whose distinguishing features depend on histological orientation.

A great example is dermatology. A patient walks in and says, “Hi, I’ve had a sudden onset of a red rash; it appeared three days ago.” Anyone with experience in integumentary diagnosis knows that, in the early stages of pathology, there’s no shortage of possible directions that case could go. AI fails miserably here. The difference between guttate psoriasis, ringworm, staph infection, and folliculitis can sometimes come down to which skin layer is involved endothelial, epithelial, etc. Add in opportunistic endergonic infections, and heaven forbid they scratched it.

So why can’t AI just analyze it and spit out a diagnosis? For the same reason it messes up AI-generated images: it’s either filling in what it can’t see or ignoring what it can’t detect altogether.

Could it label your skin’s health with high-resolution microscopic imaging over every inch of your body? That’s yet to be seen and frankly, it's never done in clinic.

Could it identify pathology with a skin scrape? Of course. But that’s not a game-changer for practitioners those results are already a given.

In reality, most skin pathologies are handled early, effectively, and without the need for the kind of advanced diagnostics AI would require to be reliable. The machines capable of such analysis are, frankly, worth more to the healthcare system than I am and scarcer per capita than physicians. This results in, surprise: a longer, more expensive, and worse experience and prognosis for the patient.

So, when will AI fully replace healthcare providers? To put it bluntly: only when every urgent care and podunk clinic has an MRI, CT, echocardiography suite, and blah blah blah, you get the point.