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Build a news recommender application with Amazon Personalize

AWS Machine Learning

Delivering personalized news and experiences to readers can help solve this problem, and create more engaging experiences. However, delivering truly personalized recommendations presents several key challenges: Capturing diverse user interests – News can span many topics and even within specific topics, readers can have varied interests.

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Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care. Customer context Philips uses AI in various domains, such as imaging, diagnostics, therapy, personal health, and connected care.

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A Major Healthcare Solution Provider streamlines claims management with CafeX

CafeX

In this case study Key lessons from deploying CafeX at the Healthcare Solution Provider 1. Overview A major Healthcare Solution Provider delivers solutions to over three million providers across the entire United States. The Healthcare Solution Provider reduced call handle time by 35%.

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Making Businesses Better: Introducing New VirtualPBX Case Studies

VirtualPBX

Whether it’s a flooring manufacturer, a financial services firm, or a digital healthcare solutions company, a reliable and feature-rich communication system is vital to streamline operations and boost customer satisfaction. We liked the personalized training that came with it. The solution? VirtualPBX.

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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

The Retrieve and RetrieveAndGenerate APIs allow your applications to directly query the index using a unified and standard syntax without having to learn separate APIs for each different vector database, reducing the need to write custom index queries against your vector store.

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Pre-training genomic language models using AWS HealthOmics and Amazon SageMaker

AWS Machine Learning

They facilitate the discovery of novel gene functions, the identification of disease-causing mutations, and the development of personalized treatment strategies, ultimately driving innovation and advancement in genomics-driven fields. Lastly the model is tested against a set of known genome sequences using some inference API calls.

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Patient Engagement Mobile Apps: On Guard of Health

CSM Magazine

The global healthcare IT market is growing, poised to reach $1.8 As the number of smartphone users grows, so does its application in healthcare. A patient engagement mobile app has the potential to revolutionize healthcare delivery. Increased engagement: apps can make healthcare more engaging and interactive for patients.