Remove Accountability Remove Benchmark Remove Healthcare
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Key Benchmarks Should You Target In 2025 for your Contact Center

NobelBiz

With the advancement of the contact center industry, benchmarks continue to shift and challenge businesses to meet higher customer expectations while maintaining efficiency. In 2025, achieving the right benchmarks means understanding the metrics that matter, tracking them effectively, and striving for continuous improvement.

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Accelerate digital pathology slide annotation workflows on AWS using H-optimus-0

AWS Machine Learning

Digital pathology is essential for the diagnosis and treatment of cancer, playing a critical role in healthcare delivery and pharmaceutical research and development. This sets a new benchmark for state-of-the-art performance in critical medical diagnostic tasks, from identifying cancerous cells to detecting genetic abnormalities in tumors.

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Cohere Embed multimodal embeddings model is now available on Amazon SageMaker JumpStart

AWS Machine Learning

All text-to-image benchmarks are evaluated using Recall@5 ; text-to-text benchmarks are evaluated using NDCG@10. Text-to-text benchmark accuracy is based on BEIR, a dataset focused on out-of-domain retrievals (14 datasets). Generic text-to-image benchmark accuracy is based on Flickr and CoCo. Interested in diving deeper?

Benchmark 101
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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. Enable a data science team to manage a family of classic ML models for benchmarking statistics across multiple medical units.

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Why Next-Gen Omnichannel is the Catalyst for Value-Based Healthcare

Avaya

There’s no denying that value-based healthcare is revolutionizing how healthcare is delivered and paid for. With half of all adults—117 million people—having one or more chronic health conditions , healthcare organizations are expected to spend close to $6 billion on treatment and prevention of chronic illness.

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Evaluation of generative AI techniques for clinical report summarization

AWS Machine Learning

When summarizing healthcare texts, pre-trained LLMs do not always achieve optimal performance. We benchmark the results with a metric used for evaluating summarization tasks in the field of natural language processing (NLP) called Recall-Oriented Understudy for Gisting Evaluation (ROUGE).

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Reduce conversational AI response time through inference at the edge with AWS Local Zones

AWS Machine Learning

Their applications span a variety of sectors, including customer service, healthcare, education, personal and business productivity, and many others. Prerequisites To run this demo, complete the following prerequisites: Create an AWS account , if you dont already have one.

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