November 28, 2025

Cryptographic Lineage for Clinical AI: Meeting the Demands of a High Risk Domain

As AI tools enter clinical environments, regulators, health systems, and scientific communities increasingly require transparency and accountability.

As AI tools enter clinical environments, regulators, health systems, and scientific communities increasingly require transparency and accountability. AI in healthcare is considered a high risk category, which means developers must demonstrate how models were trained, updated, evaluated, and monitored.

Studies highlight major issues including inconsistent implementation strategies, lack of standardisation, concerns around safety, and unclear documentation of datasets.
Source: https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913 022 08215 8

The Importance of Lineage and Monitoring

For AI to be deployed in mission critical healthcare environments, institutions must be able to show

Dataset origin
Data cleansing and preparation
Model training and tuning history
Evaluation results
Update histories
Post deployment performance and bias monitoring

Many AI tools lack robust plans for ongoing evaluation. A recent analysis of deployed clinical models notes that only a minority include comprehensive surveillance.
Source: https://arxiv.org/abs/2506.05701

Cryptographic Proofs Create Trustworthy AI

Zero Knowledge methods and cryptographic provenance systems can provide verifiable lineage without exposing any sensitive information.
Source: https://link.springer.com/chapter/10.1007/978 3 031 51063 2 8

With this approach, institutions can prove that

A model version corresponds to a documented training process
The training dataset came from authorised sources
Evaluation procedures were followed
Monitoring checks continue after deployment

Regulators, auditors, and partner institutions can verify the integrity of a model without accessing patient level data.

Ethical and Regulatory Alignment

Researchers have identified the core principles of ethical data handling as provenance, protection, purpose, preparation, and privacy.
Source: https://link.springer.com/article/10.1007/s44163 025 00266 0

Cryptographic lineage supports all five. It positions AI as a transparent and responsible tool that can satisfy clinical, institutional, and regulatory requirements.