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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

Onno – Simplifying Your Medical Documents. Struggling to understand a doctor’s letter or a radiology report? Onno provides an easy-to-understand translation of your medical documents. Simply upload any medical paperwork, and the AI, vetted by medical professionals, will clarify the medical jargon so you can grasp the content fully. You can access a free summary, while the comprehensive version, which includes detailed explanations of all terms, recommended questions for your next medical appointment, and advice on subsequent steps, is priced at €18.50. There's no need for registration or creating an account, ensuring a completely anonymous experience that adheres to GDPR guidelines and operates seamlessly in your browser. The service is available in both German and English. Currently, Onno is undergoing validation through two clinical studies at Uniklinikum Dresden in Germany. With more than 60,000 reports translated and over 90% of users finding it beneficial, it stands out as a highly utilized and reliable medical translation resource. Additionally, Onno was awarded the Deutscher KI-Startup-Preis 2025 by DIE WELT, highlighting its exceptional impact in the field. This innovative approach not only enhances patient understanding but also facilitates better communication between patients and healthcare providers.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

No images available

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

$18.50
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 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 No 
Webinars No 
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

Simply Onno GmbH

Founded

2024

Country

Germany

Website

www.simply-onno.com

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 

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