Democratizing AI in biomedical image classification using virtual reality

Artificial intelligence models can produce powerful predictive computer vision tools for healthcare. However, their development simultaneously requires computational skill as well as biomedical expertise. This barrier often impedes the wider utilization of AI in professional environments since biomedical experts often lack software development skills. We present the first development environment where a user with no prior training can build near-expert level convolutional neural network classifiers on real-world datasets. Our key contribution is a simplified environment in virtual reality where the user can build, compute, and critique a model. Through a controlled user study, we show that our software enables biomedical researchers and healthcare professionals with no AI development experience to build AI models with near-expert performance. We conclude that the potential role for AI in the biomedical domain can be realized more effectively by making its development more intuitive for non-technical domain experts using novel modes of interaction.