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arXiv · 2111.08165

RapidRead: Global Deployment of State-of-the-art Radiology AI for a Large Veterinary Teleradiology Practice

Michael Fitzke·Conrad Stack·Andre Dourson·Rodrigo M. B. Santana·Diane Wilson·Lisa Ziemer·Arjun Soin·Matthew P. Lungren·Paul Fisher·Mark Parkinson
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Abstract

This work describes the development and real-world deployment of a deep learning-based AI system for evaluating canine and feline radiographs across a broad range of findings and abnormalities. We describe a new semi-supervised learning approach that combines NLP-derived labels with self-supervised training leveraging more than 2.5 million x-ray images. Finally we describe the clinical deployment of the model including system architecture, real-time performance evaluation and data drift detection.

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Michael Fitzke, Conrad Stack, Andre Dourson, Rodrigo M. B. Santana, Diane Wilson, Lisa Ziemer, Arjun Soin, Matthew P. Lungren, Paul Fisher, Mark Parkinson. 2021-11-09. RapidRead: Global Deployment of State-of-the-art Radiology AI for a Large Veterinary Teleradiology Practice. https://arxiv.org/abs/2111.08165

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