Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Language Understanding (LUIS) is an advanced machine learning service designed to incorporate natural language capabilities into applications, bots, and IoT devices. It allows for the rapid creation of tailored models that enhance over time, enabling the integration of natural language features into your applications. LUIS excels at discerning important information within dialogues by recognizing user intentions (intents) and extracting significant details from phrases (entities), all contributing to a sophisticated language understanding model. It works harmoniously with the Azure Bot Service, simplifying the process of developing a highly functional bot. With robust developer resources and customizable pre-existing applications alongside entity dictionaries such as Calendar, Music, and Devices, users can swiftly construct and implement solutions. These dictionaries are enriched by extensive web knowledge, offering billions of entries that aid in accurately identifying key insights from user interactions. Continuous improvement is achieved through active learning, which ensures that the quality of models keeps getting better over time, making LUIS an invaluable tool for modern application development. Ultimately, this service empowers developers to create rich, responsive experiences that enhance user engagement.
Description
We have been pioneers in the development of clinical NLP platforms and their applications for over 15 years. This has resulted in high precision and accuracy. Our core competency is to interpret unstructured notes accurately and at scale. Tested on billions of real clinical notes and documents. AI that can explain with context, reasoning, and evidence for output. NLP with medical knowledge infused with 4M+ entities and 50M+ relationships. Innovative Machine Learning (ML), & Deep Learning(DL) models were used to build this NLP. Use a foundation of rich ontologies and clinician-specific terminologies. We can understand, interpret, and extract context & significance from the inconsistent, inconsistent, and non-standard data contained in medical documents. Our clinical domain experts continually infuse knowledge graphs to our NLP by mapping all clinical entities and their relationship between them. We have more than 4,000,000 entities and 50,000,000 relationships.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Azure CLU
Yes
BotCore
Yes
Dydu
Yes
Geomant
Yes
Geomant Wallboard
Yes
Ideta
Yes
Microsoft Entra ID
Yes
Neo Enterprise Assistant Platform
Yes
QnA Maker
Yes
Quickwork
Yes
Integrations
Azure CLU
No
BotCore
No
Dydu
No
Geomant
No
Geomant Wallboard
No
Ideta
No
Microsoft Entra ID
No
Neo Enterprise Assistant Platform
No
QnA Maker
No
Quickwork
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
www.luis.ai/
Vendor Details
Company Name
RAAPID INC
Founded
2022
Country
United States
Website
www.raapidinc.com
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No
Product Features
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No