Category: Healthcare

In this post, we discuss Health Kaki, a generative AI health companion using the Amazon Bedrock foundation model (FM), and highlight how the team that developed Health Kaki navigated the challenges of scaling from concept to real-world implementation.

In this post, we discuss the AI Genomic Schema Harmonizer, a generative AI–powered application that revolutionizes how laboratories prepare genomic data for submission to public repositories.

What if a Medicaid agency could make sure that their leadership and staff had access to a reliable, single source of truth for their data in one unified platform? The implementation of an operational data store (ODS) presents a viable solution. This post explains the architectural choices available with Amazon Web Services (AWS) to effectively create and maintain an ODS.

Dr. Gao Wang’s innovative research at Columbia University, powered by AWS cloud computing, represents a cutting-edge approach to understanding Alzheimer’s disease through functional genetics. Read this post to learn more.

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.