Tag: Machine Learning

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.

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 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.

The AWS Open Data Sponsorship Program makes high-value, cloud-optimized datasets publicly available on AWS. This quarter, AWS released 34 new or updated datasets from Impact Observatory, The Allen Institute for Brain Science, Common Screens, and others, which are available now on the Registry of Open Data in the following categories.

Partners are playing a key role in the continued digital transformation of public sector organizations. Public sector customers are asking for ways to increase the speed, accessibility, security, and resiliency of their systems and data. As we look forward, here’s what I’m expecting to see for partners supporting public sector customers this year.

As we begin the new year, the AWS worldwide public sector (WWPS) team wanted to share a few of our predictions for public sector technology in 2023. We hope these predictions will help guide and inspire you as you continue your digital transformation journey this year.

The First Street Foundation, a nonprofit research and technology group, is committed to making climate risk information accessible, simple to understand, and actionable for individuals, governments, and industry. As part of the Amazon Sustainability Data Initiative (ASDI), AWS invited Dr. Ed Kearns, the chief data officer of First Street Foundation, to share how AWS technologies and open data are supporting their mission to provide accurate and up-to-date information on climate related risks.

This year, the Intelligent Transportation Society (ITS) World Congress brought together more than 6,000 industry professionals from 64 countries to discuss ways to advance the deployment of intelligent transportation technologies to save lives, improve mobility, promote sustainability, and increase access to communities across the globe. For the event, ITS organized a Global Innovation Competition sponsored by AWS to encourage the development of innovative solutions that address priority themes using cloud technology. Learn more about the winners and how they’re using AWS to transform transportation.

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.

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.