AWS Public Sector Blog
Category: Artificial Intelligence
Using AI for intelligent document processing to support benefit applications and more
Each year, US federal, state, and local government agencies spend a significant part of their budgets on various social and safety net programs. Tens of millions of residents apply for these benefits every year. In these applications, documents—in various sources, formats, and layouts—are the primary tools for application assessment. Artificial intelligence (AI) technology can accelerate and simplify the application review process, improving both the case worker and applicant experience. Learn how public sector agencies can leverage AI offerings from AWS, like Amazon Textract and Amazon Comprehend, to process multiple documents in benefit application use cases in an intelligent document processing (IDP) workflow.
4 ways AWS Partners are using AI/ML to drive public sector transformation
As investments and adoption of artificial intelligence (AI) and machine learning (ML) continue to rise, there is tremendous potential for improved citizen experiences in the public sector. As government, education, and nonprofit organizations seek solutions for their challenges, AWS Partners are at the forefront of helping to solve those problems using AI and ML. Discover four AWS Partners using AI/ML to better society and improve lives.
Large scale AI in digital pathology without the heavy lifting
Pathology is currently undergoing a transformation. While microscopes still dominate many workflows, digital pathology combined with artificial intelligence (AI) is disrupting the space. AI tools can complement expert assessment with quantitative measurements to enable data-driven medicine. Ultivue is a healthcare technology (HealthTech) company that provides high-quality multiplex immunofluorescence assays and large-scale, AI-based computational pathology—built on AWS.
Helping prevent sudden cardiac arrest in young athletes with AI
Sudden cardiac arrest (SCA) is the number one cause of death for student athletes and the leading cause of death on school campuses. The nonprofit Who We Play For (WWPF) advocates for SCA prevention through advocacy, automated external defibrillator (AED) placement, cardiopulmonary resuscitation (CPR) training, and heart screenings, which include low-cost electrocardiogram (ECG) screenings from physicians that are experts in pediatric ECG interpretation. To scale their efforts, WWPF collaborated with AWS to build a ML solution to help extend the chance to get screened for SCA to every young person, potentially saving many lives each year.
AMILI helps advance precision medicine by building microbiome library on AWS
AMILI is a healthcare technology (HealthTech) company based in Singapore that seeks to advance precision medicine and personalized health and nutrition by harnessing the potential of the microbiome. AMILI uses artificial intelligence (AI) and machine learning (ML) on AWS to comprehensively quantify and characterize gut microbiomes. AMILI aims to build and curate the world’s largest multi-ethnic Asia microbiome database.
Amazon Connect helps departments of motor vehicles modernize call centers
In the last few years, many state motor vehicle departments agencies quickly transformed their processes and adopted new procedures to accommodate changes caused by the COVID-19 pandemic, like social distancing, contactless interactions, decreased staffing, and other constraints. Now, agencies can build upon these changes by modernizing their systems with intelligent automation—transitioning from reactive to proactive engagements with their citizens. Learn how to use AWS to connect and retrieve data either from an enterprise on-premises database or other third-party integration that allows for both a modernized outreach or an inbound customer experience.
AWS selected for U.S. Department of Defense Joint Warfighting Cloud Capability contract
In 2021, the U.S. Department of Defense (DoD) announced the creation of the Joint Warfighting Cloud Capability (JWCC) contract—a multi-vendor acquisition vehicle designed to make cloud services and capabilities available at all classiﬁcation levels and across all security domains, from the enterprise to the tactical edge. JWCC will enable the DoD to fully leverage the capabilities of the cloud to meet current and future mission initiatives. Further, JWCC is key to enabling critical warfighter capabilities, such as the Joint All-Domain Command and Control (JADC2), and the DoD Artificial Intelligence and Data Acceleration Initiative (ADA). As the DoD continues to modernize the way it supports the warfighter and defends our national security, AWS is committed to supporting its critical mission.
How nonprofits reimagine work using smart technology
Nonprofit leaders today have various technical products and solutions to consider. The addition of “smart technology” to your nonprofit’s technology conversations may seem intimidating or even unfamiliar to the human-centered work that your organization does. But smart technology can help make your nonprofit’s work more human – automating burdensome tasks for your teams and directing their creativity and bandwidth to what really matters: your mission. Learn how nonprofits can use AWS to develop smart tech to innovate for their communities.
3 ways tax agencies can use AI on AWS
To gain operational efficiencies and reduce workload burdens on employees, some state finance and tax agencies are leveraging robotic process automation (RPA) on AWS. RPA is a software tool that integrates with almost any system or application and performs manual, repetitive, time-consuming tasks. Tax agencies can use AI and ML to support the sheer size and scale of data they manage and to access and analyze all types of data with ease, including voice, video, and streaming data. Find out three ways AI and ML are creating measurable outcomes for tax agencies.
Predicting diabetic patient readmission using multi-model training on Amazon SageMaker Pipelines
Diabetes is a major chronic disease that often results in hospital readmissions due to multiple factors. An estimated $25 billion is spent on preventable hospital readmissions that result from medical errors and complications, poor discharge procedures, and lack of integrated follow-up care. If hospitals can predict diabetic patient readmission, medical practitioners can provide additional and personalized care to their patients to pre-empt this possible readmission, thus possibly saving cost, time, and human life. In this blog post, learn how to use machine learning (ML) from AWS to create a solution that can predict hospital readmission – in this case, of diabetic patients – based on multiple data inputs.