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ease
features
design
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

Established in Chicago, Illinois, PatientIQ provides a platform for healthcare providers, medical device manufacturers, life sciences companies, and payers to enhance their practices through data-driven medicine. It is recognized as the largest collaborative platform for healthcare professionals aimed at improving patient outcomes. By equipping healthcare providers with cutting-edge technology, PatientIQ fosters a culture of data-driven medical practice. In the competitive landscape of the U.S. healthcare market, all parties involved face mounting pressure to demonstrate their value effectively. A key factor in determining "value" lies in the objective measurement of patient outcomes. However, quantifying these outcomes presents challenges that are costly, complex, and fraught with technological obstacles. Despite these difficulties, outcomes represent the most significant currency in the future of value-based healthcare. Thus, a clear and reliable solution to systematically measure, analyze, and benchmark outcomes among various stakeholders presents a significant opportunity for growth in the digital health sector. As the industry evolves, the need for such innovative solutions will only become more pronounced.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS AI Services
AWS App Mesh
Amazon Comprehend
Care Director
EPIC HRMS
Intergy EHR
MEDITECH BCA
NextGen Healthcare EHR
Oracle Health Population Health Management
athenaClinicals
eClinicalWorks

Integrations

AWS AI Services
AWS App Mesh
Amazon Comprehend
Care Director
EPIC HRMS
Intergy EHR
MEDITECH BCA
NextGen Healthcare EHR
Oracle Health Population Health Management
athenaClinicals
eClinicalWorks

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
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

PatientIQ

Country

United States

Website

www.patientiq.io/about

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

Electronic Data Capture

Audit Trail
CRF Tracking
Data Entry
Data Verification
Distributed Capture
Document Imaging
Document Indexing
Forms Management
Remote Capture
Study Management

Patient Engagement

Appointment Scheduling
Care Planning
Collaboration
Messaging
Mobile Access
Patient Education
Patient Portal
Personal Health Record
Progress Tracking
Self Management

Alternatives

Alternatives