Category: Amazon Comprehend Medical
Healthcare customers use Snowflake to store all types of clinical data in a single source of truth. One method for gaining insights from this data is to use Amazon Comprehend Medical, which is a HIPAA-eligible natural language processing service that uses machine learning to extract health data from medical text. Learn how the Snowflake Data Cloud allows healthcare and life sciences organizations to centralize data in a single and secure location.
When it comes to healthcare and patient data, managing and storing data involves some of the greatest challenges of any industry. Disparate input sources, the need for real-time monitoring, and HIPAA data security and regulatory compliance are all necessary to maintain sensitive and personally identifiable health records. Learn how SourceFuse’s hospital ancillary revenue insights solution helps extract, analyze, and generate business insights and KPIs using patient prescription information from thousands of e-prescriptions.
In a global pandemic, it can be hard for medical practitioners and patients to get connected and treated. Continually being on top of patients’ progress is also a challenge, along with scarcity of doctors who themselves are affected by the pandemic. Learn about a reference architecture from Capgemini that uses AWS machine learning services to enable doctors and patients to interact with the least amount of physical contact, while also improving efficiency in treatment management, tracking, and auditing.
Medical coding helps providers maintain patient records and obtain reimbursement for services. Unfortunately, the process is complicated, time-consuming, and prone to error. Learn how ClearScale developed a solution that increases the efficiency and accuracy of the coding process. Powered by AWS Machine Learning, the application translates recorded medical appointment notes, and uses the information to generate more accurate medical codes.
Using Amazon Comprehend Medical, Sisense, and G-Med to Create an AI-Enhanced Knowledge Base to Combat COVID-19
As COVID-19 began to sweep the globe, organizations of all shapes, sizes, and missions sought every available tool in the fight to save lives and limit the scope and spread of the pandemic. One of the key tools at their disposal was data. G-Med, the world’s largest online medical community, teamed up with AWS Competency Partner Sisense to make a plethora of COVID-19 treatment protocols easily analyzed and searchable using AWS machine learning technologies.
The healthcare industry is experiencing a global shortage of doctors, nurses, and other healthcare professionals. Telemedicine, which provides primary healthcare services to patients through remote connectivity, is one approach for addressing this challenge. SourceFuse developed an easy-to-use and secure telemedicine application called SF Medic that can be adopted by hospitals, clinics, and even single-physician practices.
How to Use Amazon Rekognition and Amazon Comprehend Medical to Get the Most Out of Medical Imaging Data in Research
Medical imaging is a key part of patient health records and clinical trial workflows. Many facilities still burn medical imaging on CDs, a time-consuming and error-prone process. Ambra Health’s automatic pixel de-identification feature uses Amazon Rekognition and Amazon Comprehend Medical APIs to allow customers to de-identify images and reduce error. Now, it’s easier than ever to deploy an integrated application fabric that elevates healthcare efficiency and care.