Category: Amazon Comprehend Medical

As the amount of health data increases, different healthcare, life sciences, population health, and public health organizations are working to modernize their data infrastructure, unify their data, and innovate faster with technologies like artificial intelligence and machine learning (AI/ML). In this blog post, we dive deep on architecture guidance that enables healthcare providers to improve patient care.

Electronic notifications of patient events are a vital mechanism for care providers to improve care coordination and promote appropriate follow-up care in a timely manner. This post shows how a combination of Amazon Web Services (AWS) technologies, like AWS Lambda, Amazon Comprehend Medical, and AWS Fargate, can effectively manage and deliver actionable data to help healthcare customers deliver electronic notifications in a secure and efficient way.

It’s time consuming for public sector organizations to sort through packed voicemail inboxes, figure out how to respond, return calls, and take detailed records on each call. So AWS developed a scalable call center solution that allows organizations to streamline the entire call process – from call intake, to generating actionable insights for response with artificial intelligence, to detailed recordkeeping and storage. This blog post guides you through how to create this task-generating cloud call center solution with Amazon Connect.

Cancer Commons is a nonprofit network of patients, physicians, and scientists dedicated to helping patients identify and access the best personalized treatment options. Erika Vial Monteverdi, executive director of Cancer Commons, describes how the AWS compute infrastructure, combined with services like Amazon Comprehend Medical, enable physicians and patients to leverage the collective knowledge of the world’s top institutions. 

As the world grapples with COVID-19, researchers and scientists are united in an effort to understand the disease and find ways to detect and treat infections as quickly as possible. Today, Amazon Web Services (AWS) launched CORD-19 Search, a new search website powered by machine learning that can help researchers quickly and easily search tens of thousands of research papers and documents using natural language questions.

In 2019, Grand River Hospital turned to AWS to build the first AWS healthcare data lake in Canada. The data lake was built to house the hospital’s sensitive patient and administrative data while retiring its legacy hospital information systems, comprised of electronic patient record and other administrative systems. Grand River Hospital in Ontario, Canada is a 580-bed community hospital with a yearly operating budget of around $400 million CAD serving a community of 600,000-650,000 people.

Amazon Comprehend Medical is a natural language processing (NLP) service that simplifies the use of machine learning (ML) to extract relevant medical information from unstructured text often found in clinical charts or doctor’s notes. Since the service launched in the AWS Canada (Central) Region in June 2019, it opened up possibilities for Canadian healthcare organizations to better serve patients. Vancouver General Hospital (VGH) and University of British Columbia (UBC) researchers are among the organizations who leverage Amazon Comprehend Medical and Amazon SageMaker, to create their own machine learning models that can triage x-rays to provide a better healthcare experience.