Asher Informatics PBC reposted this
Great presentation by Dan Buckland, MD for those looking to design Health AI/ML models. "...if we have been poorly treating a demographic or population, that will show up in the clinical data. We might not have race, gender or zip code as an identifier in the original clinical data." shared Dr Buckland. Good insights to support the need of Asher Informatics PBC AI/ML independent equity performance audits, AI-Assess. Through a funded federal research contract, we've designed a tool in which we can provide independent real-world data subgroup population testing on clinical and signal AI/ML models and products. Right now, the MVP is designed to support #oncologyAI FDA 510K submissions and enable the FDA access to the testing of an algorithms performance and therefore better evaluate an AI/ML submission. We've partnered with Gradient Health to provide data that includes race, gender, age and we're utilizing Rhino Health's federated platform to be able to pull testing data from multiple sources. If you're an oncology AI developer, we're currently conducting feedback interviews and would love to connect.