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ease
features
design
support

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Description

Amazon Comprehend Medical is a natural language processing (NLP) service compliant with HIPAA that leverages machine learning to retrieve health information from medical texts without requiring any prior machine learning expertise. A significant portion of health data exists in unstructured formats such as physician notes, clinical trial documentation, and patient medical records. The traditional approach of manually extracting this data is labor-intensive and inefficient, while automated methods based on strict rules often overlook crucial contextual details, leading to incomplete data capture. Consequently, this limitation results in valuable information remaining untapped for large-scale analytical efforts that are essential for progressing the healthcare and life sciences sectors, ultimately impacting patient care and operational efficiencies. By addressing these challenges, Amazon Comprehend Medical enables healthcare professionals to harness their data more effectively for better decision-making and innovation.

Description

Combine and liberate your disorganized health information through an interactive AI and NLP solution that provides valuable health insights for various stakeholders. This innovative technology serves Providers by hastening the data abstraction process and ensuring the clinical information validation found within notes, thus minimizing the time and costs associated with identifying care gaps, assessing the quality of care through dashboards, and producing registry reports. For Payers, it facilitates the integration and analysis of claims alongside clinical notes, enhancing the management of high-risk and high-cost member populations. In the realm of Life Sciences, this solution enables swift patient matching to clinical trials using databases alongside clinical note data, maximizing the potential of real-world clinical evidence. Ember offers a comprehensive approach that merges NLP with predictive analytics, streamlining healthcare analytics for unstructured data to boost quality, efficiency, and outcomes in the healthcare system. As a result, stakeholders can make informed decisions that lead to improved patient care and resource allocation.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS AI Services
AWS App Mesh
Amazon Comprehend
Chromosis CRM
CodeKeep
Dragit
nTireLegal

Integrations

AWS AI Services
AWS App Mesh
Amazon Comprehend
Chromosis CRM
CodeKeep
Dragit
nTireLegal

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/comprehend/medical/

Vendor Details

Company Name

MetiStream

Country

United States

Website

www.metistream.com

Product Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Product Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Alternatives

Alternatives