Category: Healthcare

In this post, we describe how AWS Partner CIMAR’s medical image management platform is enabling the rapid roll-out, scaling, and operation of the National Health Service (NHS) England’s national lung cancer program, connecting 124 acute NHS trusts and multiple mobile scanning units.

When Siriraj Medical Research Center planned their “Nanopore workshop: bacterial genome bioinformatics series” for more than 60 researchers, they faced a common challenge: how to provide consistent, high-performance computing environments for complex genomic analyses. AWS offered the solution through Amazon WorkSpaces, transforming how Siriraj Medical Research Center delivers hands-on bacterial genomics training.

In this post, we will discuss how MSBMI and CDHI joined forces to address UTHealth Houston’s reliance on faxing. The MSBMI and CDHI team—supported by UTHealth Houston Information Technology and Amazon Web Services (AWS)—built, deployed, and migrated a new solution called iDFax.

Personalized therapy for diseases such as cancer utilizes an individual’s unique genomic profile to guide treatment decisions. However, the effect and clinical significance of most genetic variants are uncertain. Accurate classification of the clinical significance of novel genetic variants requires extensive curation of peer-reviewed biomedical literature. In recent years, generative AI has demonstrated promising results in information extraction and text summarization. In this post, we explore how various AWS-native solutions can be used to create a secure, retrieval-augmented, and cost-effective biomedical chatbot designed to facilitate biocuration.

As more and more healthcare companies use their data to remain competitive, protecting patient data is as critical than ever. With increasing adoption of AI/ML models in healthcare, making sure that these technologies comply with privacy regulations such as HIPAA and GDPR has become a top priority. Amazon Bedrock is a fully managed service that provides unified access to a diverse selection of high-performance foundation models from industry-leading AI companies. In this post, we walk you through the importance of healthcare data privacy and how to use Amazon Bedrock Guardrails to safeguard sensitive information in AI-driven healthcare solutions.

Chronic diseases are a growing global health crisis. These long-term conditions, which include cardiovascular diseases, cancer, diabetes, and respiratory illnesses, are the leading cause of mortality worldwide. In this post, we explore how a patient with chronic kidney disease (CKD) was able to successfully reverse her condition by breaking down healthcare silos, taking charge of her treatment and data, and adopting a comprehensive wellness-focused approach.

This post explores the architectural design and security concepts employed by Radboud University Medical Center Nijmegen (Radboudumc) to build a secure artificial intelligence (AI) runtime environment on Amazon Web Services (AWS). Business leaders dealing with sensitive or regulated data will find this post invaluable because it demonstrates a proven approach to using the power of AI while maintaining strict data privacy and security standards.

Serving hundreds of thousands of residents in all 34 cities of the region, Orange County United Way provides a wide range of vital community services throughout Orange County, California. After working with Amazon Web Services (AWS) Partner SoftwareONE to migrate its crisis hotline to Amazon Connect in the AWS Cloud, United Way now boasts enhanced call routing, data collection, and supervisory tools. Read this post to learn more.

Public sector organizations face stringent compliance requirements, and any unauthorized access to protected health information (PHI) or personal identifiable information (PII) can result in legal penalties and reputational damage. This post aims to demonstrate how public sector customers can develop a fine-grained authorization module using Amazon Web Services (AWS) identity services, extending beyond the capabilities of traditional role-based access control (RBAC), so they can achieve compliance objectives.

In an earlier post, Build secure and scalable data platforms for the European Health Data Space (EHDS) with AWS, we discussed a reference architecture for building secure and scalable data platforms for secondary usage of health data in alignment with the European Health Data Space (EHDS) using Amazon Web Services (AWS). This follow-up post walks you through the technical implementation details for building such federated data governance and analysis platforms using AWS. Whether you are a healthcare organization, technology provider, or systems integrator, this post aims to equip you with the technical knowledge to build a secure data platform for secondary usage of health data in alignment with the EHDS Regulation.