Trained models to identify follow-up actions embedded within content of emails received.
Software to adaptively learn and boost weight good upvoters of answers on online QA forums.
Route incoming chat conversations to the appropriate service agent based on chat content.
Cluster Patients with similar features to create chronic disease management profiles.
Conversation agent to automate answering frequently asked questions using a chatbot.
Models developed for early identification and prevention of Sepsis from medical records.
Recommendation system to tag medical records (EMRs) with their appropriate ICD-10 billing codes.
Automatic identification of priority of an incoming email based on its textual content and attributes.
Trained models to identify entirely new concepts as named entities in varying domains (verticals).
Trained models to classify incoming emails into predefined labels based on email content.
Module to extract and rank relevant and highly important keywords from any given text.
Developed a solution to provide similar keywords to a provided word, concept or document.
Software model to suggest which activity to take up next (e.g. travel), based on previous preferences.
Developed tools for semantic text matching for enhanced and accurate search experience.
Evaluation of product performance based on sentiments expressed by customers in their reviews.
Software solution to identify and learn variances of different components of an email.
Conversation engine to communicate and trigger actions for chronic disease management.
Machine Learning models to link together concepts that are the same but are referenced differently.
Training corpus development from raw and unstructured data for supervised machine learning.
Recommendation system to tag medical records with their appropriate ICD-9 billing codes.