VertigoAssist is an AI-powered clinical decision support platform that pairs a conversational patient interview with a Bayesian diagnostic engine, trained on four decades of neurotology data.
Dizziness and vertigo account for roughly 5.6 million clinic visits per year across primary care, the emergency department, and otolaryngology. Incidence of vertigo, diagnostic accuracy, and the use of imaging studies vary substantially across these settings. When the underlying cause is not immediately apparent, the prudent path is a wide differential and a broad workup — imaging, vestibular testing, audiometry, and specialist consultation. The patient is well served. The system bears substantial cost and delay.
Two clinical capabilities and two operational benefits, built into a single encounter.
A guided, structured pre-visit history that captures the elements needed for vestibular differential diagnosis — without consuming clinician time at the point of care. It asks the uncommon questions and never forgets to check for central vertigo findings.
Likelihood ratios computed empirically from a four-decade subspecialty dataset — not generic LLM inference. Validated against expert clinical adjudication.
Approximately 8 minutes saved per new dizzy patient and 4 minutes per follow-up — roughly 50 hours per year. A full week back.
The breadth of structured detail captured by the interview supports higher-tier E/M coding — particularly Level 4 documentation — in a significant share of vestibular encounters.
The data, the regulatory pathway, and the clinical demand are aligned for the first time.
VertigoAssist is led by Philip F. Anthony, MD, a neurotologist in Fort Worth, Texas. The platform's diagnostic logic and clinical workflow are derived from his vestibular subspecialty practice.
We are speaking with investors, strategic partners, and ENT practices interested in early pilots. Reach out for a briefing.
philip@vertigoassist.com