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.

本研究介绍了一个名为 “Alleviate” 的机器人的不同模块，这是一个帮助患者和临床医生更好地理解彼此，以便促进最佳护理策略的人工智能聊天机器人，其可以提供个性化护理和辅助临床医生更好地了解其患者的挑战。