AWS for Industries
Tag: #healthcare
Store omics data cost effectively at any scale with AWS HealthOmics
AWS HealthOmics is a managed service designed to help healthcare and life sciences organizations manage genomic and transcriptomic datasets cost-effectively. By automating metadata management, compression, and storage class tiering, HealthOmics frees up researchers to focus on analyzing omics data instead of spending time managing it. Storage efficiency, cost optimization and ease of access to omics […]
Top-10 re:Invent 2023 Announcements Important for Healthcare and Life Sciences
Occasionally, new technologies emerge that fundamentally alter how businesses operate. But without the appropriate tools—controls, safeguards, and user experiences—the promise of new technologies can get stuck. In the past year, many have been captivated by the potential of Generative AI to revolutionize drug discovery, precision medicine, and healthcare delivery. But what tools will turn the […]
Three Takeaways from Pfizer at AWS re:Invent Keynote
Contributed by Authors: Lidia Fonseca, Chief Digital and Technology Officer of Pfizer, and Dan Sheeran, General Manager of Healthcare and Life Sciences at AWS. Pfizer applies its scientific expertise and global resources to bring vaccines and therapies to people that extend and significantly improve their lives. Last year, Pfizer treated 1.3 billion patients – that’s […]
A Healthcare and Life Sciences Guide to AWS re:Invent 2023
Throughout 2023, we’ve witnessed an acceleration of innovation at the intersection of health and technology. And with this year’s AWS re:Invent right around the corner, industry and AWS leaders are preparing to share their cutting edge technologies, use cases, and breakthroughs fueled by integrated data strategies, machine learning, and generative AI. Running November 27 through […]
How healthcare organizations can improve discharge medication safety
Medications are integral for preventing and curing illness, yet medication errors can also be a cause of harm. For example, in 1993 over 7000 patients died in the United States as a result of a medication error. As more medications become available for use, the simultaneous use of multiple medications by a single patient is […]
Multimodal Data Analysis with AWS Health and Machine Learning Services
In this blog, we show how you can leverage AWS purpose-built health care and life sciences (HCLS), machine learning (ML), and analytics services to simplify storage and analysis across genomic, health records, and medical imaging data for precision health use cases. The included reference architecture is built on AWS HealthOmics, AWS HealthImaging, and AWS HealthLake services which enable you […]
Integration of on-premises medical imaging data with AWS HealthImaging
The medical imaging industry is used to diagnose and treat various medical conditions. The medical imaging industry has experienced significant growth [1] over the past decade and is expected to continue growing in the upcoming years. This is due to the demand for diagnostic imaging services increasing with the aging population, an increase in the […]
Introducing AWS HealthImaging — purpose-built for medical imaging at scale
We are excited to announce the general availability of AWS HealthImaging, a purpose-built service that helps builders develop cloud-native applications that store, analyze, and share medical imaging data at petabyte-scale. HealthImaging ingests data in the DICOM P10 format. It provides APIs for low-latency retrieval, and purpose-built storage. Our healthcare customers tell us they want their […]
Implement FAIR scientific data principles when building HCLS data lakes
The FAIR data principles were first proposed in a seminal paper published in 2016 in the Journal Scientific Data. It was written by a group of international experts in data management and curation. To address the challenges that the research community is facing, they proposed FAIR Principles as a framework for making data more discoverable, […]
Improve Patient Safety Intelligence Using AWS AI/ML Services
Today, healthcare organizations rely on a combination of automated and manual processes to compose, review, and classify patient safety reports. These reports are entered manually by front-line clinicians into the RL Datix reporting system. This entry includes both discrete data points as well as a free-text narrative. Although the data collection process may begin with […]