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Ratings and Reviews 0 Ratings
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What is MedGEO?
MedGeo is an innovative health platform that reestablishes the connection between healthcare professionals and patients through state-of-the-art digital solutions crafted by clinicians. This initiative works in tandem with startups, healthcare providers, administrators, and industry leaders to develop software that improves clinical workflows. Backed by the expertise of distinguished global health, surgical, and medical professionals, MedGEO leverages decades of hands-on experience from over 100 countries, providing a unique perspective on healthcare technology. In modern hospitals, the hallways are often cluttered with numerous computers and tangled cords, highlighting a chaotic system where various technologies seldom interact seamlessly. As a result, healthcare personnel frequently find themselves interacting more with technology than with patients, while clinicians often allocate too much time to data entry rather than direct patient care. By optimizing processes for healthcare providers, administrators, pharmaceutical firms, and the medical asset industry, MedGEO seeks to revolutionize the healthcare experience, allowing professionals to prioritize patient care over wrestling with complicated systems. This methodology not only boosts efficiency but also contributes to improved patient outcomes in an era that is increasingly reliant on digital solutions. Ultimately, MedGeo envisions a future where technology serves as an enabler rather than a hindrance in the healthcare landscape.
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 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
MedGEO
Company Location
United States
Company Website
medgeo.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
