AWS for Industries

Category: Healthcare & Life Sciences

Achieve Healthcare Interoperability by integrating Amazon Comprehend Medical with FHIR

Healthcare interoperability is a major initiative across all stakeholders of the healthcare ecosystem, and the Fast Healthcare Interoperability Resources (FHIR) standard has opened the doors for a modern approach to sharing such information. I have frequently heard from healthcare customers that they want to make a difference in patients’ lives by sharing the most relevant […]

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Building a multi-channel, data driven patient engagement platform with AWS

In today’s digitally transformed world, it’s more important than ever to have a deeper understanding of your patient’s attitude and behavior, and to engage them with personalized content through the channels that they prefer in order to provide efficient and personalized patient care. In addition, with today’s value-based healthcare, the patient is the center of […]

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Moderna Webinar: Building the Digital Biotech Company

Moderna is advancing messenger RNA (mRNA) science to create a new class of mRNA medicines designed to direct the patient’s own cells to produce proteins that have a therapeutic or preventive benefit. Developing therapeutics and vaccines for a variety of diseases challenges process development and operations to establish agile and flexible manufacturing, capable of executing […]

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AWS Public Database program adds valuable MIMIC-III dataset for researchers

Biomedical researchers require access to accurate, detailed data. The MIT Laboratory of Computational Physiology (LCP) MIMIC-III dataset is a popular resource that captures a variety of measures longitudinally over time, across many patients, and can drive analytics and machine learning toward research discovery and improved clinical decision-making. Recently, the MIT Laboratory of Computational Physiology (LCP) […]

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Building the foundation for Lab of the Future using AWS

Life science industries are transitioning from wet lab environments to digital labs. Digital labs decrease the “time to science” and de-risk R&D portfolios. Customers see computational methods as a way to increase the performance, throughput, and effectiveness of laboratory operations. This presents opportunities around long-standing challenges with experiment reproducibility and the ability to address lab […]

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