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arxiv:2111.08165

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

Published on Nov 9, 2021
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Abstract

A semi-supervised deep learning system evaluates canine and feline radiographs using NLP-derived labels and self-supervised training, with real-time performance and data drift detection in clinical deployment.

AI-generated summary

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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