From Medical Documents to Actionable Insights: GenAI for Pre-visit Preparation in Healthcare

Doctors often have only minutes to review a patient's history before a consultation, yet that history is spread across discharge letters, referrals, lab reports and scans in heterogeneous, frequently low-quality formats. Manual review does not scale, and in a clinical setting, extraction errors are not acceptable.
In this session, Storm Reply presents how a Generative AI document processing pipeline was taken from proof of concept to production on AWS in a real healthcare engagement. The session walks through a modular architecture that covers document classification, OCR, entity extraction and validation. Each stage can be optimized and replaced independently as foundation models evolve.
The session then addresses what it takes to make the output trustworthy in a clinical context: evidence-based model selection, automated validation with confidence scoring, integration into physicians' pre-visit workflows, and a privacy-by-design approach built on synthetic data.
You will leave with a practical understanding of the architecture, the evaluation framework behind it, and the lessons learned in moving Gen AI document processing into a regulated healthcare environment.