The Dangers of Online Diagnoses

In this digital age of internet and AI, it is turned to everywhere. Including in the medical field.

Leaving aside the topic of medical students using AI to learn things vital to your career–a whole another topic–the first thing people do when they find they have trouble with their health is google or ChatGPT their symptoms.

Which, of course, lists all the possibilities–including the worst, vey unlikely ones.

While cyberchondriasis–excessive, compulsive online searching for health information that leads to increased anxiety, distress, and fear about potential illnesses, often worsening health concerns rather than resolving them–is an extreme of that, even in less severe cases it is a problem.

People are convinced that they have only that certain disease, making it harder for doctors to diagnose and treat. Patients come in with misconceptions that take time and energy to resolve.

In this way, in diagnosing, AI can be more of a bane than a boon. Especially depending on the data used to train the model–whether it is biased, incomplete or noisy.

MBH/AB

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Very relevant point. Online searches and AI can support awareness, but without clinical context they often amplify anxiety and misconceptions. Diagnosis still requires trained judgment, examination, and evidence—technology should assist clinicians, not replace them.

AI has improved medical diagnosis, but patients self diagnosing and trusting AI over doctors is becoming a concern.

Great post

AI can inform healthcare, but without clinical context and guidance, it often amplifies fear rather than delivering clarity.