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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

BEKhealth provides an innovative clinical research platform, known as the BEKplatform, which leverages artificial intelligence to streamline the extraction, interpretation, and standardization of both structured and unstructured electronic medical record data, encompassing various elements such as lab results, diagnoses, physician notes, pathology reports, and PDFs. This integrated system creates a searchable, longitudinal patient graph designed to assist life sciences and healthcare organizations in swiftly pinpointing protocol-eligible patients while enhancing trial feasibility, site selection, and recruitment processes. By utilizing advanced deep learning techniques and natural language processing, BEKhealth transforms chaotic clinical data into precise, actionable insights, allowing for the generation of sophisticated queries and patient cohorts. This method not only identifies more qualified candidates compared to traditional manual chart reviews but also provides real-time reports and dashboards that facilitate informed decision-making across research networks, ultimately improving the efficiency and effectiveness of clinical trials. The ability to generate these insights in real-time is a game-changer for organizations striving to maximize their research potential.

API Access

Has API Yes 

API Access

Has API No 

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

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

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/comprehend/medical/

Vendor Details

Company Name

BEKhealth

Founded

2020

Country

United States

Website

www.bekhealth.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 

Product Features

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