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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.

APIs 114
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Build a medical imaging AI inference pipeline with MONAI Deploy on AWS

AWS Machine Learning

AWS, NVIDIA, and other partners build applications and solutions to make healthcare more accessible, affordable, and efficient by accelerating cloud connectivity of enterprise imaging. AHI provides API access to ImageSet metadata and ImageFrames. AWS and NVIDIA have come together to make this vision a reality. get("body").decode('UTF8')

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Automatically generate impressions from findings in radiology reports using generative AI on AWS

AWS Machine Learning

In order to run inference through SageMaker API, make sure to pass the Predictor class. pre_trained_model = Model( image_uri=deploy_image_uri, model_data=pre_trained_model_uri, role=aws_role, predictor_cls=Predictor, name=pre_trained_name, env=large_model_env, ) # Deploy the pre-trained model.

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The Rapid Rise of Virtual Health Agents in Patient Access

SmartAction

The COVID-19 pandemic is exposing frailties in our already strained US healthcare system. For healthcare providers, this sheds a stark light on what has been apparent for some time – that measures must be taken to ease the burden on healthcare workers, while also ensuring the general public has access to routine and essential health services.

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Integrate Amazon Lex and Uneeq’s digital human platform

AWS Machine Learning

Having worked with brands across numerous verticals such as UBS (financial services), Vodafone (telecommunications ), and Mentemia (healthcare), Uneeq helps customers enable innovative customer experiences powered by Amazon Lex. Amazon API Gateway. Access to the following AWS services: Amazon API Gateway. AWS Lambda. Amazon Lex.

APIs 83
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Move Amazon SageMaker Autopilot ML models from experimentation to production using Amazon SageMaker Pipelines

AWS Machine Learning

Autopilot training jobs start their own dedicated SageMaker backend processes, and dedicated SageMaker API calls are required to start new training jobs, monitor training job statuses, and invoke trained Autopilot models. We use a Lambda step because the API call to Autopilot is lightweight. script creates an Autopilot job.

Scripts 77
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Identify key insights from text documents through fine-tuning and HPO with Amazon SageMaker JumpStart

AWS Machine Learning

Organizations across industries such as retail, banking, finance, healthcare, manufacturing, and lending often have to deal with vast amounts of unstructured text documents coming from various sources, such as news, blogs, product reviews, customer support channels, and social media. Healthcare and life sciences. Demo notebook.

Scripts 71