Faster diagnosis and accelerated treatment plans for oncology patients though a global integrated platform

Digital Twin for precision medicine
Customer Challenge

The customer wanted a hyper-scaled AI platform that serves multiple use cases in oncology. The customer also wanted a solution that meets the demands of enterprise workloads and in compliant with global data compliance regulations.

Solution Implemented

Developed a cloud-native/ container-native hyper-scaled AI platform that allowed the customer to have total control over the compute and storage resources across the AI pipeline (the solution, hosted on Azure, is capable of being provisioned on any cloud). The solution uses metadata catalog that allows the seamless search of AI assets such as models, data, parameters, and hyperparameters, besides providing provenance and reproducibility and improve collaboration across teams.

Outcome Delivered
  • Customer was able to move from 80+ Deep Learning models in short time
  • Helped creating one of highest accuracy model for auto contouring in the industry with a dice coefficient of 0.9.
  • Improved data processing time by over 70%, thereby allowing faster diagnosis and better predication accuracy.
  • Solution is compliant to all regional data compliance requirements
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