A growing collection of OraDigit work across imaging order quality, PET quantification, PET response tracking, denial reduction, workflow automation, and future clinical concordance analytics.
Each case study shows the clinical problem, workflow challenge, OraDigit solution, product connection, and future development path.
A rules-driven and AI-assisted workflow designed to improve imaging order quality, reduce prior-authorization friction, and support cleaner PET/CT ordering.
A longitudinal PET workflow for comparing baseline and follow-up studies, tracking SUV change, response category, and future PETQuant confidence integration.
A glucose-aware PET quantification workflow that supports FDG PET/CT comparability by reviewing acquisition context, glucose level, uptake time, and SUV reliability.
A future analytics module for comparing reports, physician interpretations, response categories, and workflow variation across imaging cases.
Future case studies will document scheduling optimization, documentation improvement, clinical AI assistant workflows, and imaging operations dashboards.
This section can later host PDF summaries, implementation notes, pilot reports, technical briefs, screenshots, and workflow diagrams for each OraDigit product.
OraDigit case studies should grow as the platform grows. The page is designed so new product work can be added without rebuilding the structure.