##  Artificial Intelligence

#  Reducing Orthopedic Costs with Synthetic Data

 [ Back ](https://digica.com/index.php?Itemid=930)

##  Overview

To optimize surgical processes, hospitals need accuracy and efficiency—missing or incorrect orthopedic tools can lead to longer operations and increased costs. A major orthopedic tool manufacturer sought to easily and accurately identify trays and loose tools at any point in the surgical supply chain, improving visibility and minimizing expenses.

##  Objectives

- ![](https://digica.com/images/23/svg/circle.svg)

    Build and train a detector that can **identify various trays and orthopedic tools** using a mobile phone in a hospital environment.

 ![Reducing Orthopedic Costs with Synthetic Data](https://digica.com/templates/yootheme/cache/77/Reducing%20Orthopedic%20small-7738ca0f.jpeg)

##  Results

- ![](https://digica.com/images/23/svg/circle.svg)

    Delivered a **synthetic data creation and training pipeline** that powers a **computer vision surgical object recognition tool**, currently being trialed in US hospitals.
- ![](https://digica.com/images/23/svg/circle.svg)

    Due to the speed and cost-effectiveness of training, and the high levels of accuracy achieved, the application was **commercially launched** with a major orthopedic tool manufacturer in early 2023.

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