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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.

What is Oracle Health Clinical Digital Assistant?

Healthcare professionals are encouraged to prioritize direct patient care rather than administrative paperwork, fostering a sense of fulfillment in their medical practice, regaining personal time, and enhancing the quality of care through a stronger emphasis on physician-patient interactions. The Oracle Health Clinical Digital Assistant functions as an AI-powered voice assistant that effectively captures key elements of conversations between physicians and patients, processes the gathered information, and generates notes within the Oracle Health electronic health record system for prompt physician review. Users can communicate in natural language to access patient data and execute regular clinical tasks with ease. Additionally, it formulates initial clinical notes based on the interactions and information provided, ready for the physician’s assessment and approval. By leveraging voice commands, healthcare providers can seamlessly update and amend patient records, ensuring that clinical documentation is both precise and current. This cutting-edge tool is designed to simplify the documentation workflow, enabling physicians to dedicate more time to patient interactions and less to bureaucratic duties, ultimately enhancing the overall healthcare experience. The introduction of such technology not only improves efficiency but also strengthens the patient-care relationship, highlighting the essential role of communication in effective medical practice.

Media

Media

Integrations Supported

PayZen

Integrations Supported

PayZen

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

RAAPID INC

Date Founded

2022

Company Location

United States

Company Website

www.raapidinc.com

Company Facts

Organization Name

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/health/clinical-suite/

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

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