project screenshot 1
project screenshot 2
project screenshot 3
project screenshot 4
project screenshot 5
project screenshot 6

Med-AI-Safe

A secure medical trial matching system powered by Nillion's secure computation technology

Med-AI-Safe

Created At

ETHGlobal Bangkok

Winner of

World - World Pool Prize

Prize Pool

Project Description

roblem Statement Medical research requires handling sensitive patient data while maintaining privacy and compliance with healthcare regulations. Traditional systems expose private health information to multiple parties, creating privacy risks and potential HIPAA violations.

Solution This platform uses Nillion's secure computation to process sensitive medical data while maintaining complete privacy. It enables multi-party computation where different stakeholders (patients, researchers, hospitals) can participate in clinical trials without exposing underlying patient data.

How it's Made

Features

  1. Secure Trial Matching Age-based eligibility verification Symptom pattern matching Treatment duration assessment Privacy-preserving patient scoring
  2. Multi-Party Computation Patient data remains encrypted Researchers get aggregated insights Hospitals maintain oversight Zero knowledge of individual records
  3. Privacy-Preserving Access Levels Patients: Trial eligibility and effectiveness scores Researchers: Aggregated trial matches and response scores Hospitals: Safety monitoring and trial oversight
background image mobile

Join the mailing list

Get the latest news and updates