Case Study, Machine Learning, Mobile App, UI/UX Design, Web App

Case Study: A Machine Learning Web & Mobile App Supporting Mental Health

A Machine Learning Powered Web And Mobile App For Mental Health

Web and Mobile App Development, Machine Learning Development

Our client is a startup founded by a sports psychologist, a former combat engineer, U.S. Army Drill Instructor, and a veteran with 12 years of military experience. Four years ago, the client became an entrepreneur with a vision to create a web and mobile application that supports mental health.

For this job, the Topflight team built a personalized content recommendation app that helps individuals maintain emotional health and improve their time management, decision making, and goal setting. Users input their daily emotions (journaling) via text or voice, through the online platform or their mobile iOS/Android device, liking or disliking articles and famous quotes.

  • Duration:
    October 2017 – Present
  • Platform:
    Web, iOS, Android
  • Technology Stack
    MySQL, Laravel, ReactJS, PWA, NLTK, TensorFlow, RESTful services with Flask

An App To Help Users Create Better Personal Experiences

The concept is an application that gives users the type of support that comes from confession, therapy, or the guidance of a school counselor. They use voice or text inputs to express their concerns, frustrations, problems, and issues.

In return, the system applies machine learning and artificial intelligence (AI) tools to understand and respond to their needs. To succeed, it has to react like a human listener, provide an environment that is safe and non-judgmental, and deliver useful guidance to the user.

Our Development Work

The solution that we developed matches a web and mobile front-end design with a backend that uses artificial intelligence to learn user preferences and suggest helpful reading materials. The app delivers articles and famous quotes, based on its predictions about what will produce positive changes.

The users journal about their daily mental state as honestly as they can, answer questions, read and rate the suggested content, and express their responses as likes and dislikes.

The recommendation system we built integrates two types of machine learning platforms (a K Nearest Neighbors algorithm and Restricted Boltzmann Machine). It learns about users and content in real time to improve the accuracy of recommendations, classifications, and predictions.

Future Improvements

Learning goes both ways. As the AI system learns more from users, it makes better recommendations, which helps the user make better personal choices and experience better outcomes.

We plan to make that process even faster and the insights more potent as we build the dataset. We will continue to make the system smarter, and train it to classify content better with tools like the NSA API.

We also plan to ask even better questions, including after users read an article, which could also serve as a feature to measure engagement and comprehension.

 

 

 

 

 

Topflight Apps is a team of UI/UX designers, product designers, full-stack developers, and ex-founders of companies. Together, we build web and mobile apps that solve our clients’ problems in the most multidisciplinary and innovative ways possible.  We specialize in natural language processing, machine learning, and artificial intelligence software for healthcare and ecommerce.

 

Contact Topflight today and we’ll discuss your next project! We help the world’s most innovative companies build amazing products.