Clinical text mining using the Amazon Comprehend Medical new SNOMED CT API

Favorite Mining medical concepts from written clinical text, such as patient encounters, plays an important role in clinical analytics and decision-making applications, such as population analytics for providers, pre-authorization for payers, and adverse-event detection for pharma companies. Medical concepts contain medical conditions, medications, procedures, and other clinical events. Extracting medical

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Shared by AWS Machine Learning December 9, 2021

AWS Deep Learning AMIs: New framework-specific DLAMIs for production complement the original multi-framework DLAMIs

Favorite Since its launch in November 2017, the AWS Deep Learning Amazon Machine Image (DLAMI) has been the preferred method for running deep learning frameworks on Amazon Elastic Compute Cloud (Amazon EC2). For deep learning practitioners and learners who want to accelerate deep learning in the cloud, the DLAMI comes pre-installed

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Shared by AWS Machine Learning December 9, 2021

AWS computer vision and Amazon Rekognition: AWS recognized as an IDC MarketScape Leader in Asia Pacific (excluding Japan), up to 38% price cut, and major new features

Favorite Computer vision, the automatic recognition and description of documents, images, and videos, has far-reaching applications, from identifying defects in high-speed assembly lines, to intelligently automating document processing workflows, and identifying products and people in social media. AWS computer vision services, including Amazon Lookout for Vision, AWS Panorama, Amazon Rekognition,

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Shared by AWS Machine Learning December 7, 2021

Create and manage Amazon EMR Clusters from SageMaker Studio to run interactive Spark and ML workloads – Part 1

Favorite Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). It provides a single, web-based visual interface where you can perform all ML development steps required to prepare data, as well as build, train, and deploy models. We recently introduced the ability to visually

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Shared by AWS Machine Learning December 3, 2021

Create and manage Amazon EMR Clusters from SageMaker Studio to run interactive Spark and ML workloads – Part 2

Favorite In Part 1 of this series, we offered step-by-step guidance for creating, connecting, stopping, and debugging Amazon EMR clusters from Amazon SageMaker Studio in a single-account setup. In this post, we dive deep into how you can use the same functionality in certain enterprise-ready, multi-account setups. As described in

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Shared by AWS Machine Learning December 3, 2021

Quickly build custom search applications without writing code using Amazon Kendra Experience Builder

Favorite Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra reimagines search for your websites and applications so your employees and customers can easily find the content they’re looking for, even when it’s scattered across multiple locations and content repositories within your organization. With Amazon

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Shared by AWS Machine Learning December 3, 2021