Breast cancer is a horrible disease that affects millions worldwide. In the US and other high-income countries, advances in medicine and increased awareness have significantly improved the survival rate of breast cancer to 80% or higher. However, in many lower-income countries the survival rate is below 40%, largely due to a lack of early detection systems.¹

Advances in AI and medicine can make massive differences in beating diseases like breast cancer by extending diagnostics, enhancing pattern recognition in imaging, and deploying these resources for those who need them most.

One promising advancement for early detection breast cancer systems is the application of computer vision to medical imagery. In recent years, deep learning has improved the quality of computer vision technology tremendously by learning from data. These techniques can also be applied to radiology scans to recognize and highlight possible malignant or benign areas.

The ImageNet competition, a common image classification benchmark, illustrates the progress since the introduction of deep learning with AlexNet. (Image from papers with code)

At the Center of Data Science and Department of Radiology at NYU, researchers recently showed that a well trained Convolutional Neural Network (CNN), in tandem with radiologists’ predictions, delivered more accurate predictions than either by themselves.

These cutting-edge techniques and models are constantly being improved and shared, but after these models are created and trained, they need to be scaled.

Hospitals and radiology labs need to be able to productionize, scale, and deliver the results from these models so they can actually be leveraged in real-world scenarios. That’s where AI Infrastructure platforms like Pachyderm come into the picture.

Pachyderm gives you a powerful data-oriented machine learning platform that helps take research projects from the lab to enterprise-grade applications. Its immutable, version-controlled file system and Docker-based pipelines make it easy to build a robust platform capable of reaching millions across the globe.

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