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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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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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Evaluation of generative AI techniques for clinical report summarization

AWS Machine Learning

This is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading artificial intelligence (AI) companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API. When summarizing healthcare texts, pre-trained LLMs do not always achieve optimal performance.

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A progress update on our commitment to safe, responsible generative AI

AWS Machine Learning

Red-teaming engages human testers to probe an AI system for flaws in an adversarial style, and complements our other testing techniques, which include automated benchmarking against publicly available and proprietary datasets, human evaluation of completions against proprietary datasets, and more.

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Enable data sharing through federated learning: A policy approach for chief digital officers

AWS Machine Learning

In this post, we discuss the value and potential impact of federated learning in the healthcare field. However, the datasets needed to build the ML models and give reliable results are sitting in silos across different healthcare systems and organizations. This isolated legacy data has the potential for massive impact if cumulated.

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Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

AWS Machine Learning

In addition, they use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide an answer to the user’s request. In Part 1, we focus on creating accurate and reliable agents.

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Best practices to build generative AI applications on AWS

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, Mistral AI, Stability AI, and Amazon via a single API. Kojima et al. 2022) introduced an idea of zero-shot CoT by using FMs’ untapped zero-shot capabilities.