Our APIs

Natural language processing and computer vision APIs for your use cases and business needs.

Find the one that best suits your needs and integrate dezzai’s services in your own environment.

Text Analytics

When dealing with large volumes of documents, it is essential to organize and classify the information so you can easily find what you are looking for at any given time. Having the ability to perform this process automatically means an immense saving in time and resources.

Medical Named Entity Recognition

This API is a Named Entity Recognition (NER) system that allows the detection of named entities in a clinical text, being especially useful in Electronic Health Records (EHRs). It locates and classifies parts of the text into pre-established categories, such as diseases, treatments, symptoms, drugs, doses.

Sentiment Analysis

This API classifies documents according to the positive, negative, or neutral polarity of the language they contain.

Sentiment Analysis

This API classifies documents according to the positive, negative, or neutral polarity of the language they contain.

Question and Answering

This API returns information about an unstructured document or a set of documents as a result of a question asked in natural language.

Computer Vision

At dezzai we have decided to implement computer vision in order to derive meaningful information from images, videos or any other type of visual input in order to make recommendations and help organizations take action over their data.

DICOM-CBCT

API for the dental industry based on analysis of CBCT image processing and feature extraction algorithms. Both machine learning and deep learning processes have been used in the creation of the algorithm, the latter with the aim of training models that can detect pathologies.

Semantic Search

As a faster and easier way to find information here at dezzai, we have developed our own semantic search engine. This enables searching for the most relevant information in a corpus of documents, as well as to detecting and/or recommending documents that are similar in terms of their semantic content.

Semantic Search in medical literature

This API concept-driven search engine, based on UMLS & CIE-10, extracts information from medical scientific libraries (PUBMED, Lilacs) in order to facilitate processes such as:

1. Adverse event detection
2. SOTA summaries

If you are interested in integrating any of our APIs, please contact us at info@dezzai.com