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features
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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

Facilitate connections between healthcare entities such as hospitals, clinics, health plans, and life sciences with app developers and health data partners to create innovative digital services based on FHIR APIs. Enhance both the efficiency and safety of transitions throughout the continuum of care, whether in-patient or out-patient. Offer personalized wellness and prevention strategies tailored to at-risk individuals, fostering proactive health management. Encourage collaboration among patients, healthcare providers, and physicians to effectively address chronic conditions, leading to better management outcomes. Focus on patient-centered digital services that prioritize user experience and safety, while minimizing risks during care transitions. Utilize an enterprise-grade platform capable of managing, securing, and scaling APIs that remain agnostic to FHIR servers. Seamlessly integrate healthcare data from various sources, including internal systems, external partners, or open-source FHIR-ready resources. By swiftly launching digital services like mobile applications, advance the vision of patient-centric healthcare and enhance data interoperability, ultimately improving healthcare delivery for all. This approach not only enhances patient engagement but also drives innovation across the healthcare landscape.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS AI Services Yes 
AWS App Mesh Yes 
Amazon Comprehend Yes 
Apigee No 
Google Cloud Platform No 

Integrations

AWS AI Services No 
AWS App Mesh No 
Amazon Comprehend No 
Apigee Yes 
Google Cloud Platform Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
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 Yes 
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 Yes 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/comprehend/medical/

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

cloud.google.com/solutions/apigee-health-apix

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

Alternatives

HealthAPIx Reviews

HealthAPIx

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