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features
design
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

ROOK provides an all-encompassing API solution that facilitates the smooth integration of health data from a wide array of over 300 wearable devices and other data sources into various applications. By offering a singular integration point, ROOK removes the burden from developers of having to manage individual integrations, maintenance tasks, or address discrepancies in data for each device. It not only aggregates and processes this data but also standardizes units, resolves duplicates or missing data points, and supplies actionable, real-time health insights ready for use. Additionally, ROOK's Health Score presents a consolidated view of health by leveraging biomarker information from diverse sources, which assists in forecasting user behaviors and significant events without necessitating further analysis. Designed with a focus on security, it complies with HIPAA and GDPR standards to ensure the protection of sensitive data. Founded by a team of biomedical engineers with considerable knowledge in medical devices and hardware-software integrations, ROOK also provides expert advice and support to its clients, fostering a collaborative approach to health data management. This makes ROOK an invaluable partner for developers aiming to enhance their applications with reliable health insights.

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 

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

$399 per month
Free Trial No 
Free Version Yes 

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 No 
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

ROOK

Founded

2019

Country

United States

Website

www.tryrook.io

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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