Patient AnalyticsZKP

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Problem Statement

The challenge today is that health care data is sensitive. Traditional systems struggle to balance the need for research access with the imperative of patient privacy. Cryptographic commitments and zero-knowledge proofs offer a robust framework for secure, private transactions. We adapt this technology to health care, ensuring that patient data remains confidential while still accessible for research and facilitating analysis.

Solution

The Patient Health Records holds 2 fields - Disease (string) & Age (number). "Disease" is converted into a Groth16 zksnark (using gnark) and "Age" is converted into a Pedersen Commitment (using zkSigma). The encrypted patients are added to the ledger. This Ledger provides analytical functions like Average age of All Patients & Patient Average Age for a specific disease. For example, to find the average age of "asthma" patients:Filter patients in ledger by disease Verify(Patient.disease.zkp) == “asthma”Calculate total age of filtered patients Homomorphic addition → (PatientA.age.commitment + PatientB.age.commitment + …)Average = Total age / no. of filtered patients