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What is Healthcare Blocks?
A great starting point for your journey is Healthcare Blocks, which provides a cloud-based application hosting platform built on Linux, ensuring adherence to HIPAA regulations and the NIST cybersecurity framework. Our experienced team is committed to maintaining the security and scalability of this platform, allowing your organization to focus on the effective development and deployment of applications. For healthcare organizations that are either currently using or planning to implement Amazon Web Services (AWS), our advanced solution alleviates the complexities and manual efforts related to fulfilling the requirements of AWS's "shared responsibility model." This service successfully bridges the gap between being "HIPAA eligible" and attaining full "HIPAA compliant" status. The infrastructure incorporates Ubuntu security-enhanced virtual machines with auto-scaling features, encrypted storage, and automated security updates to ensure robust protection. Additionally, Amazon S3 is leveraged for the secure storage of uploaded files, backups, and archived datasets, which bolsters data integrity and accessibility. Support is facilitated through a standard help desk portal, with options for enhanced premium support available when needed. Moreover, our offering includes compatibility with Docker engines and Dokku PaaS, streamlining application deployment and management processes. This all-encompassing solution empowers healthcare organizations to drive innovation while maintaining high standards of security and compliance, ultimately fostering a more efficient and secure digital healthcare environment.
What is Amazon Comprehend Medical?
Amazon Comprehend Medical is an NLP service designed to adhere to HIPAA standards, employing machine learning to extract health information from medical documents without necessitating any prior expertise in machine learning from its users. A vast amount of healthcare data is found in unstructured formats, such as physicians' notes, clinical trial reports, and patient histories. Relying on traditional, manual methods for data extraction is not only time-consuming but also prone to errors, as rule-based automation often fails to capture essential contextual details, resulting in incomplete data retrieval. This lack of reliability can significantly undermine the effectiveness of large-scale analytics, which are critical for advancements in the healthcare and life sciences industries, ultimately impeding potential enhancements in patient care and operational effectiveness. By utilizing this sophisticated service, healthcare organizations can gain invaluable insights and improve their decision-making capabilities, ultimately leading to better outcomes for patients. This transformative approach represents a significant leap forward in how health data can be leveraged for greater efficiency and efficacy in medical practices.
Integrations Supported
AWS AI Services
AWS App Mesh
Amazon CloudWatch
Amazon Comprehend
Amazon S3
Amazon Web Services (AWS)
Docker
Microsoft Teams
Slack
Integrations Supported
AWS AI Services
AWS App Mesh
Amazon CloudWatch
Amazon Comprehend
Amazon S3
Amazon Web Services (AWS)
Docker
Microsoft Teams
Slack
API Availability
Has API
API Availability
Has API
Pricing Information
$159 per month
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Healthcare Blocks
Company Location
United States
Company Website
www.healthcareblocks.com
Company Facts
Organization Name
Amazon
Date Founded
1994
Company Location
United States
Company Website
aws.amazon.com/comprehend/medical/
Categories and Features
Categories and 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
