Remove APIs Remove Healthcare Remove Personalization
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Intelligent healthcare forms analysis with Amazon Bedrock

AWS Machine Learning

Generative artificial intelligence (AI) provides an opportunity for improvements in healthcare by combining and analyzing structured and unstructured data across previously disconnected silos. Generative AI can help raise the bar on efficiency and effectiveness across the full scope of healthcare delivery.

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How healthcare payers and plans can empower members with generative AI

AWS Machine Learning

Generative AI technology, such as conversational AI assistants, can potentially solve this problem by allowing members to ask questions in their own words and receive accurate, personalized responses. After a successful authentication, a REST API hosted on API Gateway is invoked.

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7 Reasons ChatGPT Alone Can’t Deliver the Customer Service You Need

CCNG

That can become a compliance challenge for industries like healthcare, financial services, insurance, and more. Unclear ROI ChatGPT is currently not accessible via API and the cost of a (hypythetical) API call are unclear.

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Elevate healthcare interaction and documentation with Amazon Bedrock and Amazon Transcribe using Live Meeting Assistant

AWS Machine Learning

The Live Meeting Assistant (LMA) for healthcare solution is built using the power of generative AI and Amazon Transcribe , enabling real-time assistance and automated generation of clinical notes during virtual patient encounters. What are the differences between AWS HealthScribe and the LMA for healthcare?

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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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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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Build a read-through semantic cache with Amazon OpenSearch Serverless and Amazon Bedrock

AWS Machine Learning

It excels at providing personalized responses drawn from a pool of past interactions, making sure that each reply is relevant and tailored to travelers’ needs. This can lead to better insights, personalized recommendations for clients and improved risk management by firms. This could improve outcomes and reduce waste in the system.