Autonomous AI screening flags unreliable Lyme test results, boosting sensitivity to 95.7%

Computational point-of-care sensors can significantly improve access to diagnostics by enabling rapid patient testing outside centralized medical facilities. These tests rely on machine learning models to make diagnostic predictions, but such inference models are susceptible to hallucinations and may produce erroneous outcomes. As a result, their limited reliability has partially hindered the broader adoption of computational sensors in health care settings.