Radiologists increasingly rely on AI for screening and diagnosis. InferTrust™ creates cryptographic proof that AI findings are authentic, supporting malpractice
AI-assisted radiology tools are making their way into clinical workflows, flagging suspicious findings on imaging studies, prioritizing worklists, and providing quantitative measurements. When these AI outputs influence clinical decisions, the stakes are high: a missed finding or a false positive can change a patient's treatment path.
InferTrust™ creates a cryptographically verifiable record for each AI-assisted radiology event. This includes the model version and configuration active at the time of inference, the input feature hash (derived from the imaging data without storing the image itself), the AI output (finding classification, confidence score, localization data), the decision action taken (CLINICAL_FLAG, CLINICAL_CLEAR, or CLINICAL_ESCALATE), and the policy and threshold that governed the decision.
When a malpractice claim alleges that an AI finding was missed or improperly acted upon, the organization needs to prove exactly what the AI produced and what happened next. Application logs are mutable and may not survive legal scrutiny. InferTrust™'s tamper-evident records provide verifiable proof that the AI output was presented to the radiologist, that it reflected a specific model version and policy, and that subsequent clinical actions are documented in the decision chain.
Radiology AI tools classified as Software as a Medical Device (SaMD) under FDA oversight face requirements around performance monitoring and post-market surveillance. See InferTrust™ FDA Enforcement for details. InferTrust™'s decision records support these requirements by providing a verifiable audit trail of every inference event, enabling organizations to demonstrate ongoing model performance and governance to FDA reviewers.