NLP Solution for Medical Research Databases
Our easy-to-use solution lets medical researchers query data using natural English language either as text or voice and converts it into a structured SQL request.
Example: Find all patients, either male from 20 to 25 years old or female from 30 to 35, who were diagnosed with diabetes within the last 12 months and started treatment with Fiasp two months after the first diagnosis.
We have also developed a rich user interface and chatbot which communicates with users to supplement the NLP parser. The speech system continuously refines its ability to “hear”, understands a wide variety of accents and automatically adjusts to a particular customer’s requests.
- Deep Recurrent Neural Networks
- Sequence to Sequence Architecture
- Speech Recognition
- Noise Reduction
- Dependency Parser
- Word Lemmatization and Tokenization
- Reinforcement Learning
- Entity Recognition
- .NET
- Python
- C++
- PyTorch
- Flask
- StarSpace
- Numpy
- WaveNet
- Audacity
- JavaScript
- SASS
- Dragula
- AngularJS
- Flow
- Redux
- Peg.js
- MS SQL Server