Category: Healthcare

Leaders in the healthcare industry are increasingly recognizing how a data-driven approach can help them improve member satisfaction. Many of them have begun their transformative journey to adopt a member-first approach and unify disparate data silos. They recognize that the journey toward a unified system is strategic and will pay enormous dividends when completed. However, […]

Healthcare providers are challenged every day with providing customer care that meets each individual need. With location data, healthcare providers can help to accelerate patient care in multiple parts of their organization. Providers can use location data to enrich and standardize their database to ensure it contains accurate location information to help improve interoperability between […]

Vignesh Shetty, Senior Vice President and General Manager of Edison AI & Platform at GE Healthcare, joins Taha Kass-Hout, MD, MS Vice President and Chief Medical Officer at Amazon Web Services (AWS), to discuss strategies for building a modern data strategy to fuel innovation and improve patient care. GE Healthcare provides medical technology, pharmaceutical diagnostics, […]

Securely sharing clinical research data with collaborators and efficiently managing data access is a recurring challenge that clinical research teams face. Amazon S3 Access Points enable clinical researchers and healthcare IT teams to efficiently create, share, and maintain scalable access to clinical data in a shared Amazon S3 bucket at the individual user level. Introduction […]

Population genomics initiatives amass a multitude of clinical, omics, and phenotypic data from diverse participants. This data is critical to a range of healthcare use cases, including biomarker discovery, drug repurposing, patient stratification, and precision medicine. However, strict data security and regulatory frameworks often make large-scale data migration unfeasible, creating a fragmented data landscape that […]

New AWS for Health Guidance: Multi-modal and Multi-omics The new era of personalized health relies on data to guide more customized patient treatments, therapeutics, and diagnoses. Genomics sits at the core of personalized health, and by taking into account the individual variability among people and diseases, clinicians can create more personalized care journeys and targeted treatments. […]

Introduction Training medical computer vision (CV) models requires a scalable compute and storage infrastructure. Training a medical CV model is unique compared to training a CV model in other domains, as we described in the first part of this blog series. In this second post, we show you how we scale a medical semantic segmentation training […]

Introduction Computer vision (CV) and machine learning (ML) has been playing an increasingly import role in the field of medical imaging and radiology in the past decade. CV is the field that uses computers and programs to replicate human vision abilities such as recognition, classification, detection and measurement. Thanks to the advancement of deep learning […]

Increasingly digital populations are demanding more from healthcare services. A recently published Deloitte survey of 2,000 Australians reports 70% willing to use virtual healthcare services, and 80% ready to share their health data in a digitally enabled health system. This behavioral shift is testing the limits of legacy healthcare systems; sending governments and healthcare organizations […]

re:MARS is back! This year, re:MARS is happening in person from Las Vegas, NV from June 21-24, delivering cutting edge talks, demos, workshops, and networking opportunities, as well as a rich on-demand option for virtual attendees. The event is offering 100+ sessions spanning Machine Learning, Automation, Robotics, and Space tracks, with six of them focused […]