GravityMedShield

GravityMedShield - Human-in-the-Loop Recursive Medical De-identification Medical AI is experiencing an unprecedented boom, but it faces a massive regulatory wall: **Patient Privacy**. The bottleneck of AI in healthcare is access to medical data Hospitals have Petabytes of quality medical data, but are not allowed to share them without proper PHI sanitation. PHI that is Protected Health Information. - Names - Dates - birth dates - Biometrics - Visuals - Unique Identifying traits To train models or share medical data, datasets must be strictly de-identified. But standard tools fall short and eventually fail. The solution GravityMedShield - a human in the loop medical de-identification studio built on antigravity powered by three specialized agents Agent A: Conductor cleans metadata headers and extracts PII search terms Agent B: Visual Specialist - locates burned in PHI data in image frames using state of the art gemini 3.5 flash - and a local model inside a hospital Agent C: Pixel Masker - redacts visual PHI in dice files Reviewers can run this application locally and review side-by-side unredacted and sanitized data approve, reject, rework manually or with AI The game changer is what makes this application future proof: recursive self-improvement. Whenever a reviewer performs manual corrections, the system memorizes these actions for future images with that device fingerprint. This way the AI learns from human supervisors continuously refining its deidentification skills.