Whether it’s a harvesting robot trained to identify and pick apples at peak ripeness or a surgical robot that performs key imaging and diagnostics during surgery, robotic automation can increase accuracy, reduce costs, and optimize for efficiency. AI-powered robotics companies rely on accurate, custom built datasets to train their products to perform important, and often delicate, tasks at the level of humans.
Improving Patient Outcomes with AI-Trained Surgery Robot
This robotics company is focused on improving patient outcomes and reducing costs to healthcare systems through the integration of advanced computer vision. Their robotics are designed to provide advanced imaging and boost diagnostic accuracy during surgery. CloudFactory supports their goals by labeling surgical images gathered by a surgery robot to train it further.
- Tagging images for key objects such as tissue, instruments, needles, and thread at the pixel-level using Dataloop’s image annotation tool.
- Maintaining client standards of 97%+ accuracy across a variety of complex use cases to train the robot for use in surgery.
We have been through a full production cycle of data sent through CloudFactory. We’ve fed that back into our model, trained it, deployed it and seen much, much better results and model accuracy.
Chief Technology Officer
Software as a Service Company
AI is transforming healthcare by arming practitioners with more information at the right times to make better /decisions and fewer errors.
Image annotation holds great promise for these centuries-old industries that rely heavily on visual data and are ripe for AI innovation.
Your in-house data scientists shouldn't be doing tedious data labeling work for machine learning projects. They should be focusing on more important innovation.
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