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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 DeepScribe?

DeepScribe utilizes cutting-edge AI technology to effortlessly document conversations between healthcare providers and patients, ensuring that medical notes are generated automatically, which allows clinicians to dedicate more time to patient interaction rather than paperwork. The user-friendly mobile application captures these clinical discussions and transcribes them in real time, while the proprietary AI processes the transcript to sort the medical details into a standardized note, seamlessly integrating it into the clinician's electronic health record system. In contrast to conventional scribes, dictation systems, or other methodologies, DeepScribe's ambient functionality ensures that the documentation process does not interfere with the patient experience or disrupt the overall clinical workflow. Healthcare professionals can engage with their patients as they normally would, later reviewing and approving the notes within their EHR after the consultation. Furthermore, DeepScribe not only takes care of documentation and charting but also suggests appropriate diagnostic codes based on the extracted information from the visit. By leveraging DeepScribe’s intuitive, effective, and advanced AI scribe, clinicians are empowered to rediscover the fulfillment of providing care in medicine, ultimately enhancing the patient experience. This innovative approach transforms the way healthcare professionals manage their documentation responsibilities.

Media

Media

Integrations Supported

Integrations Supported

DrChrono
Elation Health
Practice Fusion
athenaOne

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

DeepScribe operates at a fraction of the cost of an in-person or virtual scribe. Specific pricing varies based on size of practice. Contact us for pricing details, or schedule a demo

Supported Platforms

SaaS

Supported Platforms

SaaS
iPhone
iPad

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard 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

DeepScribe

Date Founded

2017

Company Location

United States

Company Website

www.deepscribe.ai/

Categories and Features

Categories and Features

Clinic Management

Not specified

Dictation

Not specified

Healthcare AI

Not specified

Medical Transcription

Not specified

Speech Recognition

Not specified

Speech to Text

Not specified

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