Yet this skill has faded. We jump to scans and labs before the story is fully explored — and it is hard to master the pertinent questions across every specialty. DxFlow brings an experienced clinician’s reasoning to any complaint: it guides a focused, high-yield history and lays out a transparent, dangerous-first differential — so your time goes to reasoning, not recalling. You make the final call, with the basis for every step in view.
Differential diagnosis
Medical decision-making is hard — it takes sound reasoning and consistency, under pressure, on every patient.
The diagnosis usually lives in the history — but taking a thorough, pertinent one on every patient, under time pressure, is hard.
The time-critical, can’t-miss conditions have to be considered in every scenario — and they’re the easiest to overlook.
Committing to a plan takes reasoning you can trust — backed by medical evidence and years of experience, not guesswork.
Leaning on general AI is risky — it’s inconsistent and can confidently hallucinate. Medicine needs something steadier.
DxFlow works the way a careful clinician does — one focused question at a time, always thinking about what could be dangerous.
Begin with the chief complaint. The intake follows traditional medical teaching for that scenario, and every next question is high-yield — each one takes you a step closer to the diagnosis.
A ranked list of diagnoses with odds updates as you answer — and the can't-miss causes are always checked first.
DxFlow recommends the next best test or action — the right test, not every test — and shows the reasoning, so you decide with a clear picture.
Both can help you think. Only one is built on checked medical knowledge, reasons the same way every time, and shows its work.
| Asking ChatGPT | DxFlow | |
|---|---|---|
| Where the knowledge comes from | A general AI trained on the whole internet | Doctors chose and checked every clue and diagnosis |
| How it decides | Predicts the most likely words | Adds up real clues like a doctor — and shows the math |
| Same question, same answer? | Can change each time | The same every time — consistent |
| Does it show its thinking? | Usually just gives an answer | Shows each diagnosis and how likely, updating as you answer |
| Can it make things up? | Yes — it can invent facts ("hallucinate") | No — only the checked medical list; it won't invent tests |
| Does it check for danger? | Might miss the scary causes | Always rules out the dangerous causes first |
| Who it's built for | Everyone, for anything | Built for clinicians and students |
| Your patients' privacy | Your text may be used to train the AI | No patient names — de-identified by design |
Physicians, nurse practitioners, and physician assistants across primary care, urgent care, emergency, and hospital medicine — an experienced reasoning partner at the point of care, especially when there's no senior colleague to turn to.
Practice structured reasoning and build the "dangerous-first" discipline, with the logic visible at every step.
No patient names are ever stored — cases are de-identified, so it's safe to use in everyday practice and teaching.
Short bio — a few lines to add
I've been in clinical practice for over 25 years, and I've made my share of mistakes. To this day I still dread misdiagnosing a case, or delaying a diagnosis and the treatment that depends on it. Medicine has progressed tremendously — MRI and CT scans, endoscopy, and a whole host of lab tests now help us reach a diagnosis. But one thing hasn't changed: the art of history taking — listening to the patient for the clues to the diagnosis.
I think of a patient who arrived with sudden abdominal pain, nausea, and diarrhea. The first explanation — gastroenteritis — seemed to fit. But something didn't: the pain was far more severe than the exam suggested, and a more deliberate history uncovered atrial fibrillation and a recent lapse in anticoagulation. That changed the differential. Instead of sending the patient home with fluids and reassurance, we pursued urgent imaging and caught intestinal ischemia before the window to act had closed.
Unfortunately, I see many of us moving away from that art and rushing to order all sorts of tests. It drives unnecessary cost and, too often, inaccurate diagnoses. Many colleagues are also turning to ChatGPT for answers. It's helpful, but inconsistent — and at times it gives grossly inaccurate, even invented, answers (technically, "hallucinations") that can be very costly. In medicine we can't allow that, even if it's rare.
So I built DxFlow: a tool that thinks the way I was trained to — dependable and deterministic. Its purpose isn't to hand you the final answer right away, but to build a reasonable differential and, above all, to make sure life-threatening conditions are never missed. It helps me order the right tests — stopping the unnecessary ones, and prompting the ones I might otherwise have overlooked.
I built it for everyone who carries that responsibility — physicians, and especially the nurse practitioners and physician assistants so often on the front line, seeing undifferentiated patients across every system, frequently without a senior colleague to turn to. DxFlow is meant to be that experienced colleague in the room, so you can act with confidence and know that you are doing what anyone else will do in that situation.
Every diagnosis, finding, and judgment in it is curated and corrected by a physician — not scraped from the internet. It's the experienced reasoning partner I wish I'd had as a resident, and the one I still want on a busy day. And it doubles as a learning tool for trainees.
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