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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

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

Text recognition made easy allows for rapid extraction of content from various types of images and digital documents. You can swiftly obtain non-selectable text from sources such as YouTube videos, PDFs, images, online courses, screencasts, presentations, webpages, and photos. Utilizing a built-in snipping tool for Mac, the process is as straightforward as taking a screenshot. Simply press CMD+Shift+2 to initiate the capture or choose the text capture option from the menu bar. The selected text will be promptly recognized and stored in your clipboard, ready to be pasted using CMD+V into notes, editors, messengers, or any other application. Additionally, you can easily scan and convert any QR code or barcode to text in just a moment. TextSniper can also enable your Mac to read text from images whenever necessary, making it a valuable tool for language learners and individuals who may struggle with reading text on screens. Furthermore, the text-to-speech functionality serves as an excellent assistive technology for those with dyslexia, enhancing accessibility and comprehension for users. With these features, TextSniper truly transforms how we interact with written content in the digital age.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS AI Services
AWS App Mesh
Amazon Comprehend

Integrations

AWS AI Services
AWS App Mesh
Amazon Comprehend

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$9.99 per month
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/comprehend/medical/

Vendor Details

Company Name

TextSniper

Country

United States

Website

textsniper.app/

Product Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Product Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

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