Why Regulating AI and digital health Bias in Healthcare Innovation Matters
This article is of interest to innovators whose technology incorporates AI which may have different levels of performance accuracy depending on the availability and access to population data.
A living systematic review of bias mitigation methods in Natural Language Processing for equitable healthcare AI
This article may be relevant to your organisation if you are using or plan to use natural language processing.
Generative Models for Augmenting Limited Sample or Biassed Healthcare Data
This article may be relevant to your organisation if you are working in areas of rare disease and the application of sample augmentation strategies is relevant.
Bias in Geolocation and Sub-Population Models versus Foundational Global Models
This article may be relevant to your organisation if you are working with localized models and global models to assess their performance and fit with your solution.
How Post Market Surveillance Interacts with Statistical and Computational Models of Drift in AI Models
This article may be relevant to your organisation if you are working with evolving ML/AI and have insights that could help shape regulations ensuring adaptive models are both safe and explainable
An Exploration of AI Explainability Techniques for Understanding Clinical Trust
This article is of interest to innovators whose technology incorporates or could benefit from Explainable AI (XAI).