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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

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a unified API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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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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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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Knowledge Bases for Amazon Bedrock now supports custom prompts for the RetrieveAndGenerate API and configuration of the maximum number of retrieved results

AWS Machine Learning

In this post, we discuss two new features of Knowledge Bases for Amazon Bedrock specific to the RetrieveAndGenerate API: configuring the maximum number of results and creating custom prompts with a knowledge base prompt template. You can now choose these as query options alongside the search type. First, we set numberOfResults = 5.

APIs 139
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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. Regulations in the healthcare industry call for especially rigorous data governance.

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Exploring summarization options for Healthcare with Amazon SageMaker

AWS Machine Learning

In today’s rapidly evolving healthcare landscape, doctors are faced with vast amounts of clinical data from various sources, such as caregiver notes, electronic health records, and imaging reports. In a healthcare setting, this would mean giving the model some data including phrases and terminology pertaining specifically to patient care.