Amazon SageMaker Canvas is a visual tool that allows medical clinicians to build and deploy machine learning (ML) models for image classification without coding or specialized knowledge. It offers a user-friendly interface for selecting data, specifying output, and automatically building and training the model. This approach simplifies the process of developing ML models for medical…
Generative AI is being adopted by healthcare and life sciences customers to help extract valuable insights from data. Use cases include document summarization and converting unstructured text into standardized formats. Customers are looking for performant and cost-effective models, as well as the ability to customize them. This article explains how to deploy a Falcon large…
Prior authorization is a crucial process in healthcare that involves the approval of medical treatments before they are carried out. The Da Vinci Burden Reduction project has rearranged the prior authorization process into three implementation guides aimed at reducing complexity. The Coverage Requirements Discovery (CRD) guide focuses on determining authorization requirements using Clinical Decision Support…
Accenture has collaborated with AWS to create Knowledge Assist, a generative AI solution that helps enterprises connect people to information efficiently. Using AWS generative AI services, Knowledge Assist can comprehend vast amounts of unstructured content and provide precise answers to user questions. By improving knowledge retention and reducing training time, this solution has proven to…
This blog post discusses the importance of time series forecasting in data-driven decision-making and explores a robust time series forecasting model using Amazon SageMaker. It highlights the use of MLOps infrastructure for automating the model development process and explains the steps involved in training and deploying the model. The post also provides an overview of…