I study how clinical evidence, biomarkers, and emerging technology can sharpen medical decisions—from intensive care to the classroom.
Research thesis
Better decisions begin where biological signals, clinical judgment, and responsible technology meet.
Research map
The work is organized by the questions it asks—not simply by where it was published.
Medical AI
Diagnostic performance of GPT-4 across clinical specialties, AI in time-critical care, and observable AI literacy in medical education.
Top-five diagnostic match after laboratory and instrumental data were added.
Critical care
IL-6, sTREM-1, CRP and related biomarkers for diagnosis, prognosis, and pathogen differentiation in critically ill adults.
Cardiovascular inflammation
Galectin-3 and echocardiographic changes across acute COVID-19, heart-failure phenotypes, and post-acute disease.
Clinical & population research
Case-based learning, wound repair, tobacco-control attitudes, hygiene behavior, dietary patterns, and liver disease.
Study spotlight · Medical AI
A retrospective observational study compared GPT-4’s differential diagnoses with physicians’ final diagnoses across 340 clinical cases.
Selected output archive
Articles, posters, preprints, and presentations. Select a research area to trace the work across formats.
Teaching
Invited Lecturer · Department of Internal Medicine
Lecturer · Tbilisi, Georgia
Invited Lecturer · Faculty of Medicine
About
Nino Gvajaia, MD, is an Internal Medicine resident at Wellstar Health System and a graduate of Tbilisi State Medical University. Her work spans medical artificial intelligence, intensive-care biomarkers, cardiovascular inflammation, medical education, and population health.
Her approach centers on clinically meaningful questions, collaborative investigation, and translating complex evidence into decisions that improve patient care.