AI Radiology Vision

Overview

AI Radiology Vision is a HIPAA-compliant healthcare AI template that gives radiologists a reporting copilot for chest, mammography, and other structured reads — STAT-first worklist, rule-based RADS classification, critical-results workflow, and an AI-drafted impression for the radiologist to sign. Lung-RADS and BI-RADS classification with management recommendations are deterministic; the AWS Bedrock impression draft is the only AI-generated text. The critical-results loop enforces flag, communicate, and acknowledge before sign-off, all written to an immutable audit log. The template is built for HIPAA, BAA, FDA 510(k), ISO 13485, and HITRUST programs, integrates with DICOM and Orthanc for study ingestion, and ships a three-role RBAC console (technologist, radiologist, admin). Pixel-level image inference is a production computer-vision integration, honestly disclosed rather than simulated. Customize inside VertiComply, generate the full React + FastAPI + Postgres stack with compliance scaffolding, then export to GitHub. No platform lock-in.