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What is Genospace?

At Genospace, we understand that while progress in genomics is driving the advancement of precision medicine, the task of effectively scaling its implementation remains a significant hurdle. Our objective is to close this gap by leveraging our innovative platform, which is designed to convert biomedical data into actionable insights that are readily available to all, especially those involved in patient care. By empowering clinicians and researchers with crucial information, we enable them to make informed decisions while working toward our shared vision of using complex molecular data to improve patient outcomes and accelerate drug development and research processes. The importance of extensive population data for drug discovery and research is paramount in this endeavor. Take advantage of cohort-driven analyses through the Genospace platform to bolster your research projects. With a dedicated focus on clinical trial research, our platform effectively connects disparate patient data with intricate trial requirements, ensuring faster patient recruitment. Additionally, we aim to seamlessly weave genomic medicine into routine clinical practices, thus simplifying the integration of genomic insights into everyday healthcare. By collaborating closely, we can redefine the limits of patient care and research, ultimately fostering a more informed healthcare ecosystem.

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.

Media

Media

Integrations Supported

AWS AI Services
AWS App Mesh
Amazon Comprehend

Integrations Supported

AWS AI Services
AWS App Mesh
Amazon Comprehend

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

Genospace

Company Location

United States

Company Website

www.genospace.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/comprehend/medical/

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

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