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Description

Efficiently merge the multiomic information of patients with their health records to provide more tailored care solutions. Implement specialized data repositories to facilitate extensive analyses and foster collaborative research initiatives on a population-wide scale. Expedite research processes by leveraging adaptable workflows and comprehensive computational tools. Ensure the safeguarding of patient privacy through adherence to HIPAA standards, complete with robust data access and logging mechanisms. AWS HealthOmics empowers healthcare and life science organizations, along with their software collaborators, to securely store, retrieve, and analyze diverse omics data, such as genomic and transcriptomic information, ultimately yielding valuable insights that enhance health outcomes and propel scientific advancements. Manage and evaluate omics data for extensive patient cohorts to discern how variations in omics relate to phenotypic expressions within the population. Develop consistent and accountable clinical multiomics workflows designed to minimize turnaround times while boosting efficiency. Seamlessly incorporate multiomic assessments into clinical trials aimed at evaluating new therapeutic candidates, thereby enhancing the overall drug development process. By harnessing these innovative approaches, organizations can ensure a deeper understanding of patient health and contribute to groundbreaking research findings.

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.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS AI Services Yes 
AWS App Mesh No 
Amazon Comprehend No 
Amazon Web Services (AWS) Yes 

Integrations

AWS AI Services Yes 
AWS App Mesh Yes 
Amazon Comprehend Yes 
Amazon Web Services (AWS) 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) Yes 
Online Support Yes 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/healthomics/

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/comprehend/medical/

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 

Alternatives

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