Tag: healthcare

Pathology is currently undergoing a transformation. While microscopes still dominate many workflows, digital pathology combined with artificial intelligence (AI) is disrupting the space. AI tools can complement expert assessment with quantitative measurements to enable data-driven medicine. Ultivue is a healthcare technology (HealthTech) company that provides high-quality multiplex immunofluorescence assays and large-scale, AI-based computational pathology—built on AWS.

A key focus for the Department of Health and Human Services (HHS) and state Medicaid agencies is making sure those eligible for Medicaid maintain coverage and supporting transition to alternatives. Medicaid agencies need to conduct outreach to make their millions of members aware of the process for redetermination. With cloud-based tools from AWS, state agencies can conduct this outreach using no code/low code, serverless, elastic services that can scale to two billion text messages a day. In this blog post, learn how to set up a multi-lingual, interactive SMS message campaign that can automatically verify and update member information on file based on member responses.

AMILI is a healthcare technology (HealthTech) company based in Singapore that seeks to advance precision medicine and personalized health and nutrition by harnessing the potential of the microbiome. AMILI uses artificial intelligence (AI) and machine learning (ML) on AWS to comprehensively quantify and characterize gut microbiomes. AMILI aims to build and curate the world’s largest multi-ethnic Asia microbiome database.

Medical software development companies Digithurst and Telepaxx worked together to create an end-to-end cloud solution chain handling administration of patient data and their radiological scans; viewing and editing of scans; as well as long-term archiving. To develop a scalable, secure, and cost effective solution chain supporting further innovations, the companies turned to the AWS Cloud.

Earlier this year, US President Joe Biden set a goal to end cancer as we know it by improving prevention, screening, diagnosis, and treatment. To answer this call, AWS is expanding its ongoing work with the Children’s Brain Tumor Network (CBTN). Together, AWS and the CBTN will enable researchers and clinicians to share and analyze medical record, imaging, genomic, and other data in near real-time to speed development of new therapies for pediatric brain cancers.

Supporting and protecting the healthcare workforce is an essential investment in the continuity of health services. That’s why AWS is choosing to focus on training, retaining, and deploying healthcare workers with the launch of a new AWS Healthcare Accelerator. This is AWS’s first ever global healthcare cohort focused on workforce development.

Diabetes is a major chronic disease that often results in hospital readmissions due to multiple factors. An estimated $25 billion is spent on preventable hospital readmissions that result from medical errors and complications, poor discharge procedures, and lack of integrated follow-up care. If hospitals can predict diabetic patient readmission, medical practitioners can provide additional and personalized care to their patients to pre-empt this possible readmission, thus possibly saving cost, time, and human life. In this blog post, learn how to use machine learning (ML) from AWS to create a solution that can predict hospital readmission – in this case, of diabetic patients – based on multiple data inputs.

Singapore’s National University Health System (NUHS) collaborated with Integrated Health Information Systems (IHiS), Singapore’s technology agency for the public sector, to develop the OneNUHS App. The mobile healthcare application extends healthcare services beyond the hospital, providing telehealth services like video consultations with doctors and more. To accelerate time-to-launch, save costs, and support reliable access for Singaporeans, the OneNUHS app uses AWS.

Healthcare providers and healthcare systems want to modernize their healthcare data exchanges so they can better analyze and gain more insight from their clinical data. In this walkthrough, learn how to use AWS to migrate legacy healthcare messaging data into HAQM HealthLake, which can use artificial intelligence (AI) and machine learning (ML) to discover meaningful and actionable healthcare information embedded in unstructured text.

Japan’s High Energy Accelerator Research Organization (KEK), is a Nobel Award-winning Inter-University Research Institute, and one of the world’s leading accelerator research institutes. To further help researchers understand human biology, AWS and KEK recently announced a collaboration to develop GoToCloud, a KEK-led cloud platform that makes protein analysis faster and more cost-effective, boosting KEK’s research efforts and improving our understanding of disease. This initiative has also accelerated the digital transformation of Japan’s scientific research infrastructure, helping scientists discover new medicines and produce world-class research results using cloud technology.