This literature review involves the use of AI communication facilitators to detect mood disorders such as bipolar disorder, a psychiatric condition in which patients experience drastic mood shifts. Due to the ill-defined nature of the disorder, it is difficult for even a psychiatrist alone to be confident with their diagnosis. Changes in mental and mood state are often highly subjective and difficult to pinpoint through short-term surveys and psychiatric consultations. For many patients, diagnosis and treatment based on trial-and-error is unavoidable. A timely and thorough diagnosis and treatment plan is associated with the need for an equal involvement of both the patient and the psychiatrist throughout the process. This conclusion is reached through a detailed assessment of current interventions for (i) the ill-defined nature of the disorder, and (ii) the trial-and-error requirement for medication and diagnosis. As a result, I propose the implementation of an AI communication facilitator that can aid in the appropriate diagnosis and treatment of bipolar disorder by embodying the shared decision-making model. I propose that the model can be broken down into specific critical decision points with considerations made for each party involved in the process, aligning with the service blueprint model. I conclude by emphasizing the importance of AI in bipolar disorder diagnosis and treatment due to its ability to embrace patient heterogeneity, and bridge the gap between mental healthcare and human-AI interaction.

翻译：本文综述了利用人工智能交互促进器检测情感障碍，例如双相情感障碍（一种精神疾病，患者会经历剧烈的情绪波动）。由于该障碍的定义不明确，即使仅由精神科医生进行诊断也很难自信确认诊断结果。心境和情感状态的变化通常高度主观且难以通过短期调查和精神科会诊来准确定位。对于许多患者而言，基于试错的诊断和治疗是不可避免的。及时和全面的诊断和治疗计划需要患者和精神科医生在整个过程中拥有平等的参与。通过对当前处理（i）疾病的不明确性和（ii）药物和诊断的试错需求的干预方案的详细评估，得出了这个结论。因此，我提出实现一个AI通信促进器，可以通过体现共享决策模型来帮助治疗和适当诊断双相情感障碍。我建议该模型可被分解为特定的关键决策点，并针对涉及到的各方进行考虑，符合服务蓝图模型的要求。最后，强调了人工智能在双相情感障碍诊断和治疗中的重要性，因为它能够拥抱病人的异质性，并弥合心理保健和人机交互之间的鸿沟。