Category: Artificial Intelligence

As the amount of health data increases, different healthcare, life sciences, population health, and public health organizations are working to modernize their data infrastructure, unify their data, and innovate faster with technologies like artificial intelligence and machine learning (AI/ML). In this blog post, we dive deep on architecture guidance that enables healthcare providers to improve patient care.

Without proper documentation, unhoused individuals face overwhelming barriers to stability and opportunity. But new technologies and tools address these problems while helping the organizations who serve vulnerable populations. One innovative solution called Kiip, powered by Amazon Web Services (AWS), takes a unique approach to this problem by empowering individuals with access and control over their own personal, vital documents.

Healthcare organizations across the nation are working to address clinician burnout and are more constrained than ever. That’s why Netsmart, an industry leader in electronic health records for human services and post-acute care, and Amazon Web Services joined forces to advance artificial intelligence for community-based care providers, through the development of an AI Data Lab. By combining the scale and power of AWS with the Netsmart CareFabric® platform, Netsmart is driving intelligent automation, generative AI, predictive analytics, natural language processing and risk models to improve care delivery and outcomes for community-based care providers.

Amazon Web Services (AWS) is launching its first Education Accelerator, giving EdTech founders the support and mentorship they need to bring innovative solutions to market by leveraging the power of data, analytics, AI/ML and the cloud.

The education sector has gone through a transformative technological change in the last few years. First, the pandemic created a rise in e-learning solutions, as teachers and students adopted digital platforms for communicating, teaching and learning, and managing academic information. These solutions show that students all over the world can get quality education over the […]

This walkthrough explores how to leverage Amazon Forecast to derive valuable business insights in satellite communications use-cases. Operations teams can quickly see accurate satellite capacity forecasts on a per beam basis. The benefits include lower cost via provisioning just the right amount of bandwidth, and a more streamlined customer experience since users will be less impacted by weather or surge events.

Since wildfires can double in size and intensity every three to five minutes, early detection and reduced response times are essential. Cloud technologies, including artificial intelligence (AI) and machine learning (ML), can help with this. Learn a high-level architecture to create a solution with AWS that uses AI to identify and classify wildfire smoke imagery and then rapidly alert and inform first responders about the location and condition of a fire incident.

GraphQL is a query language and server-side runtime system for application programming interfaces (APIs) that prioritizes giving clients exactly the information they request and no more. GraphQL can help public sector customers focus on their data and provide ways to explore the data in their APIs. Learn a reference architecture using serverless technologies that you can use to build GraphQL-enabled solutions in the AWS GovCloud (US) Regions to unify data access in real-time and simplify operations.

As the daily volumes of document submissions increases for government organizations, intelligent document processing (IDP) solution architectures must absorb spikes in requests without creating delays or other impact for the users. In cases where the processing volume exceeds the limits of the resources available in an AWS Region, organizations can distribute the workloads across multiple regions to increase the document processing throughput. This post presents high-level architecture guidance built around Amazon Comprehend to create a distributed document processing workload that can overcome the challenges of unpredictable request patterns.

What if paper forms could be processed at the same speed as digital forms? What if their contents could be automatically entered in the same database as the digital forms? Medicaid agencies could analyze data in near real time and drive actionable insights on a single dashboard. By using artificial intelligence (AI) and machine learning (ML) services from AWS, Medicaid agencies can create this streamlined solution. In this walkthrough, learn how to extract, analyze, and interpret relevant information from paper-based Medicaid claims forms.