Prediabetes AI Benchmark
Can AI help people understand when to get screened, what to do next, and when to seek urgent care? I designed 100 synthetic patient scenarios to find out.
Binya Liu · Physician-Scientist · Clinical AI
Drawing on clinical medicine, research, and teaching, I develop rigorous AI evaluations and practical tools to support better care and healthier, happier lives.
Science for Health. Joy for Life.
Explore my work →Selected Projects
Can AI help people understand when to get screened, what to do next, and when to seek urgent care? I designed 100 synthetic patient scenarios to find out.
A planned patient-friendly health application exploring screening guidance, risk communication, and safer next steps.
Featured Research · Prediabetes AI Benchmark
Prediabetes often has no obvious symptoms. But early screening and healthier habits can help prevent or delay type 2 diabetes.
U.S. adults estimated to have prediabetes
CDC · 2026U.S. adults with prediabetes who don't know they have it
CDC · 2026AI agreement with predefined next steps in 80 held-out synthetic cases (74/80)
JoyBinya · Independent benchmarkThe first two figures are U.S. public-health estimates from CDC (2026) ↗ . The third is a benchmark result, not clinical accuracy.
As more people turn to AI for health information, I wanted to know whether a GPT-based model could recommend appropriate screening, judge urgency, recognize missing information, and explain the next step safely.
Across 80 unseen cases, 74 recommendations matched the predefined next steps. The model also classified all 8 cases in a small urgency check. Physician review showed why safe clinical guidance cannot be reduced to one score.
Help build trustworthy AI that encourages earlier awareness, appropriate screening, timely care, and informed choices for healthier lives.
This evaluation used synthetic scenarios. Its findings do not establish real-world clinical accuracy, safety, or improved patient outcomes. The benchmark is not a diagnostic tool or medical advice.
About Me
Medicine has shaped my life since I entered medical school at 17. Years of patient care, research, and teaching have taught me that great healthcare requires sound judgment, scientific rigor, and genuine empathy.
Today, I bring these perspectives to healthcare AI — building trustworthy evaluations and practical tools that support clinicians, empower patients, and help more people make informed decisions about their health.
Research & Publications
Selected publications exploring reproductive health, multiomics, and emerging technologies in medicine.
American Journal of Obstetrics & Gynecology
Let's Connect
Open to opportunities and collaborations in clinical AI research, evaluation, safety, and health innovation.
View my GitHub ↗