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What is Verana Health?
Verana Health functions as a sophisticated platform for real-world data, transforming both structured and unstructured elements from electronic health records into curated, de-identified, disease-specific data modules via its clinician-informed and AI-augmented VeraQ population health data engine. By consolidating information through essential partnerships with leading medical registries, such as the American Academy of Ophthalmology, Neurology, and Urological Association, the platform combines insights from over 20,000 healthcare professionals and nearly 90 million patient records, thus offering high-quality datasets in near real-time for generating real-world evidence, pinpointing clinical trial sites and subjects, monitoring clinician performance, and maintaining medical registries. Users benefit from this extensive data repository through cloud services like AWS Data Exchange and Amazon Redshift, which feature self-service API access, an intuitive dashboard, and tools for personalized cohort exploration. Additionally, the system utilizes state-of-the-art AI and machine learning algorithms alongside thorough data quality evaluations to guarantee the dependability and precision of the information supplied. This pioneering method not only streamlines data application but also significantly improves the quality of healthcare research and practice, fostering an environment where informed decisions can be made with confidence. Ultimately, Verana Health exemplifies how technology can bridge the gap between clinical data and actionable insights, shaping the future of medical research.
What is RAAPID?
For over 15 years, we have led the way in creating clinical NLP platforms and exploring their various applications, achieving remarkable levels of precision and accuracy in the process. Our primary expertise lies in accurately interpreting unstructured medical notes on a large scale, having tested our systems against billions of genuine clinical documents. We have developed AI that not only provides output but also elaborates with context, reasoning, and supporting evidence. Our NLP technology is enriched with over 4 million entities and more than 50 million relationships, thanks to the integration of extensive medical knowledge. By employing advanced Machine Learning (ML) and Deep Learning (DL) models, we have constructed a robust NLP framework built upon comprehensive ontologies and specialized clinician terminologies. This allows us to effectively comprehend, interpret, and extract meaningful insights from the often inconsistent and non-standard data present in medical records. Our clinical domain experts continuously enhance our NLP capabilities by integrating knowledge graphs that detail the connections between all clinical entities, ensuring our systems remain at the forefront of medical data interpretation. With this relentless pursuit of innovation, we are poised to shape the future of clinical NLP further.
Integrations Supported
AWS Data Exchange
Amazon Redshift
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
Verana Health
Company Location
United States
Company Website
veranahealth.com
Company Facts
Organization Name
RAAPID INC
Date Founded
2022
Company Location
United States
Company Website
www.raapidinc.com
Categories and Features
Population Health Management (PHM)
Analytics
Cost-of-Care Analysis
Data Storage
EMR/EHR Integration
Patient Engagement
Patient Identification
Patient Risk Stratification
Patient-Reported Outcomes
Payment Bundling
Predictive Alerts
Test & Treatment Reminders
Utilization Tracking
Categories and Features
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