Demo Alleviate: Demonstrating Artificial Intelligence Enabled Virtual Assistance for Telehealth: The Mental Health Case

TL;DR

This paper introduces Alleviate, an AI-powered virtual mental health assistant designed to provide personalized, safe, and explainable support for patients and clinicians, with demonstrated capabilities for improved mental health care.

Contribution

The paper presents a modular, clinically-informed chatbot architecture that enables safe, personalized mental health support and facilitates feedback-driven improvements.

Findings

Alleviate effectively assists patients with mental health challenges.

The chatbot provides medically sound and informed interactions.

Modular design allows continuous refinement based on user feedback.

Abstract

After the pandemic, artificial intelligence (AI) powered support for mental health care has become increasingly important. The breadth and complexity of significant challenges required to provide adequate care involve: (a) Personalized patient understanding, (b) Safety-constrained and medically validated chatbot patient interactions, and (c) Support for continued feedback-based refinements in design using chatbot-patient interactions. We propose Alleviate, a chatbot designed to assist patients suffering from mental health challenges with personalized care and assist clinicians with understanding their patients better. Alleviate draws from an array of publicly available clinically valid mental-health texts and databases, allowing Alleviate to make medically sound and informed decisions. In addition, Alleviate's modular design and explainable decision-making lends itself to robust and continued feedback-based refinements to its design. In this paper, we explain the different modules of Alleviate and submit a short video demonstrating Alleviate's capabilities to help patients and clinicians understand each other better to facilitate optimal care strategies.