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.
翻译:在疫情后,面向心理健康的人工智能辅助支持变得越来越重要。提供充分的护理所需面对的各种挑战包括:(a)个性化的患者理解,(b)安全限制和医学验证的与聊天机器人患者互动以及(c)利用与聊天机器人患者交互的支持进行持续反馈的设计完善。我们提出了“Alleviate”聊天机器人,旨在协助患有心理健康问题的患者获得个性化护理,并帮助临床医生更好地了解他们的患者。Alleviate利用一系列公开可用的临床有效的心理健康文本和数据库,使其能够做出医学上合理和明智的决策。此外,Alleviate的模块化设计和可解释的决策制定适合进行强大而持续的反馈设计的完善。本文中,我们解释了Alleviate的不同模块,并提交了一个短视频,展示了Alleviate帮助患者和临床医生更好地了解对方以促进最佳护理策略的能力。