
Three healthcare AI experts who've watched millions wasted on failed projects. Dr. Harvey Castro, Dr. Junaid Kalia, Edward Marx, and various experts cover all things healthcare AI - from digital transformation to clinical reality.
Every Tuesday, we diagnose real failures, reveal what actually works, and help you avoid the expensive mistakes we've seen repeated everywhere.
Because when AI decisions affect patient care, getting it right isn't optional.
What happens when the data behind AI doesn't actually reflect the patients it's meant to help?
When 71% of training data for FDA-approved AI comes from just three states, geographic bias shifts from a technical oversight to a direct clinical liability.
The overarching signal is: we're early, it's messy, and the people closest to the work know it best.
What if the real barrier to better patient outcomes isn't the medicine — it's the infrastructure to prescribe it well?
What if the difference between a late diagnosis and a successful intervention was simply how we decode the signals of a sound wave?
You went into medicine to save lives. But somewhere between residency and the real world, you started wondering — is there more I could be doing?
Most healthcare conversations stop at disruption, but this one starts there.
What if the most powerful diagnostic tool wasn't a scan or a lab result — but a continuously learning model of your patient, built from their own data?
You already know not every AI tool belongs in your workflow. The real question is whether your filter is sharp enough to tell the difference.
Will AI eliminate primary care — or finally give primary care physicians their time back?
Signal and Symptoms Podcast