Usecases
Maria Fareri Children's Hospital deploys a diagnosis platform …
A diagnostic assistant platform called Isabel uses natural language processing and machine learning to offer possible diagnoses for physicians. Symptoms are entered into Isabel as text and the system's algorithms search through its medical database to offer likeliness of different diagnostic predictions, with claimed 95% accuracy.
TMZ generates more than 6.5m video views on …
TMZ uses Wibbitz's machine learning based video content creator to auto modify and create videos edited to maximise views for each platform. Videos can also be auto created from text using images, publicly available videos etc combining machine learning with manual intervention.
Instapaper reviews saved articles and generates clean text …
Instapaper uses Diffbot to curate content from web articles and newspapers and saves metadata to auto-sync with the app. Diffbot uses NLP and machine learning to extract content from web pages.
Disney enhances the search feature in online stores …
Disney uses Google's AutoML feature to improve online shopping experience for customers. The new feature includes image search and a model that improves from user search by mapping the likeness between different search terms and results. For example, find all the products that feature a likeness of Lightning McQueen and not just those where your favorite talking race car was …
Progressive implements mobile chatbot to answer customer service …
The auto insurance provider Progressive introduced a text chatbot to field customer service inquiries over Facebook Messenger using Microsoft Azure tools and natural language understanding.
Crisis Text Line identifies 85% of high-risk users …
The Crisis Text Line allows users in need of immediate mental health help to text a counsellor. Some of those users need emergency service intervention, so machine learning has been applied to discover relations between text message content and the requirement for immediate intervention, allowing the service to better prioritize users. The system identifies 86% of users at high risk …