Towards Selection of Large Multimodal Models as Engines for Burned-in Protected Health Information Detection in Medical Images
Researchers evaluated large multimodal models (LMMs) like GPT-4o and Gemini 2.5 Flash for detecting protected health information (PHI) in medical images. While LMMs showed improved text recognition (lower Word Error Rate) compared to traditional OCR methods, this did not always translate to higher overall PHI detection accuracy. The study found that LMMs were most effective on complex imprint patterns and offered recommendations for selecting and deploying these models in healthcare settings. AI
IMPACT LMMs show potential for improving PHI detection in medical images, particularly for complex cases, guiding future healthcare AI deployments.