Tarvinder Singh, MD

Why This Exists

At 3 AM, when you get a code stroke call, you need evidence -- not a textbook chapter. You need to know if this patient qualifies for IVT, whether the extended window applies, and which RCTs enrolled patients like yours. You need it in 30 seconds on your phone.

The stroke decision support tool matches patient data against AHA/ASA 2026 guidelines and randomized controlled trials. Every recommendation cites the original source directly.

Methodology

All guideline recommendations reference the AHA/ASA 2026 Guidelines for Early Management of Patients With Acute Ischemic Stroke. Trial data -- inclusion criteria, enrolled population distributions, and outcomes -- are extracted from the original publications, not secondary sources or review articles.

The matching engine evaluates patient data against trial criteria and computes a population fit score based on how closely the patient matches the enrolled demographics. When trials disagree, the tool shows both perspectives with clinical context.

AI Transparency

Parts of this site are built and maintained with AI assistance. If you find an error, I want to hear about it.

The simplest way to reach me is on LinkedIn.

The Book

The Future of AI in Medicine explores what happens when algorithms enter the exam room -- written by someone who has been in both the code review and the clinical conference.

Alongside the site and the book, I am also building FIRY AI.