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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.

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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. In the healthcare industry, reliability and connectivity are paramount.

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Revolutionizing large language model training with Arcee and AWS Trainium

AWS Machine Learning

Dataset collection We followed the methodology outlined in the PMC-Llama paper [6] to assemble our dataset, which includes PubMed papers sourced from the Semantic Scholar API and various medical texts cited within the paper, culminating in a comprehensive collection of 88 billion tokens. Shamane Siri Ph.D.

APIs 93
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“ID + Selfie” – Improving digital identity verification using AWS

AWS Machine Learning

The COVID-19 global pandemic has accelerated the need to verify and onboard users online across several industries, such as financial services, insurance, and healthcare. In this post, we present the “ID + Selfie” identity verification design pattern and sample code you can use to create your own identity verification REST endpoint.

APIs 74
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Build a news recommender application with Amazon Personalize

AWS Machine Learning

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. Delivering personalized news and experiences to readers can help solve this problem, and create more engaging experiences.

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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. Although the work presented here focuses on chest X-ray reports, it has the potential to be expanded to bigger datasets with varied anatomies and modalities, such as MRI and CT, for which radiology reports might be more complex with multiple findings.

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Detect real and live users and deter bad actors using Amazon Rekognition Face Liveness

AWS Machine Learning

Financial services, the gig economy, telco, healthcare, social networking, and other customers use face verification during online onboarding, step-up authentication, age-based access restriction, and bot detection. Spoof detection Face Liveness can deter presentation and bypass spoof attacks.

APIs 77