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features
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support

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Write a Review

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

Envision a partner in commercial services that seamlessly integrates with your team, which is precisely the vision behind EVERSANA. We prioritize your business objectives and offer a ready-made infrastructure designed to safeguard your investments. Our focus is on metrics and accountability, utilizing integrated and actionable data to drive performance. Our comprehensive range of services is tailored to meet diverse needs, regardless of size. EVERSANA stands out as the singular service provider capable of collaborating with life sciences innovators in any capacity. You can harness our extensive portfolio of services throughout every phase of the product life cycle, from pre-commercialization to addressing impending loss of exclusivity. By integrating our offerings, you can create customized, purpose-driven solutions to tackle challenges like market access, distribution efficiency, patient adherence, and beyond. As a catalyst in the life sciences services sector, EVERSANA eliminates the necessity of relying on various vendors or service providers. Instead, we have developed a commercial services platform designed to operate in harmony with your own processes. This ensures a streamlined approach that enhances efficiency and effectiveness across your operations.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS AI Services Yes 
AWS App Mesh Yes 
Amazon Comprehend Yes 

Integrations

AWS AI Services No 
AWS App Mesh No 
Amazon Comprehend No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/comprehend/medical/

Vendor Details

Company Name

EVERSANA

Country

United States

Website

www.eversana.com/solutions/

Product Features

Data Extraction

Disparate Data Collection No 
Document Extraction No 
Email Address Extraction No 
IP Address Extraction No 
Image Extraction No 
Phone Number Extraction No 
Pricing Extraction No 
Web Data Extraction No 

Natural Language Processing

Co-Reference Resolution No 
In-Database Text Analytics No 
Named Entity Recognition No 
Natural Language Generation (NLG) No 
Open Source Integrations No 
Parsing No 
Part-of-Speech Tagging No 
Sentence Segmentation No 
Stemming/Lemmatization No 
Tokenization No 

Product Features

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