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.

人工智能模型可以为医疗保健提供强大的预测性计算机视觉工具。然而，它们的开发同时需要计算技能和生物医学专业知识。由于生物医学专家通常缺乏软件开发技能，因此这一障碍通常会阻碍人工智能在专业环境中的更广泛应用。我们展示了第一个开发环境，在该环境中，未经事先培训的用户可以在真实世界的数据集上构建接近专家级的卷积神经网络分类器。我们的主要贡献是虚拟现实中的简化环境，用户可以在其中构建、计算和评论模型。通过受控用户研究，我们表明我们的软件使没有 AI 开发经验的生物医学研究人员和医疗保健专业人员能够构建具有接近专家性能的 AI 模型。