About the Customer
The client is a global biopharmaceutical company focused on discovering, developing, and delivering innovative medicines for patients with serious diseases. Their medicines are helping millions of patients around the world in disease areas such as oncology, cardiovascular, immunoscience, fibrosis, and others.
The Client wanted to reduce the tedious manual effort of clinicians reviewing X-rays and detecting and classifying diseases. The manual approach also led to increased false diagnoses and suboptimal outcomes. The client was using Python and R for such business cases and mostly had a manual approach. Using traditional methods of image classification was not yielding good results and manual efforts were very time-consuming and not cost-effective.
Brillio assessed their business and explored the features of AWS SageMaker. We also did a model comparison between AWS and traditional methods, aiming to migrate from traditional modeling to AWS using its cloud services.
The steps taken for analysis were as below:
The steps of the implementation and the approach:
Following Brillio’s implementation, the client was able to:
The results led to:
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