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arxiv: 2111.08165 · v1 · pith:F4TLMR57new · submitted 2021-11-09 · 💻 cs.LG · cs.CV· eess.IV

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

classification 💻 cs.LG cs.CVeess.IV
keywords deploymentdescribesystemabnormalitiesacrossapproacharchitecturebroad
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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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