AI-assisted Diagnosing, Monitoring, and Treatment of Mental Disorders: A Survey

Faustino Muetunda, Soumaya Sabry, M. Jamil, Sebastião Pais, Gael Dias, João Cordeiro
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Abstract

Globally, 1 in 7 people has some kind of mental or substance use disorder that affects their thinking, feelings, and behaviour in everyday life. People with mental health disorders can continue their normal lives with proper treatment and support. Mental well-being is vital for physical health. The use of AI in mental health areas has grown exponentially in the last decade. However, mental disorders are still complex to diagnose due to similar and common symptoms for numerous mental illnesses, with a minute difference. Intelligent systems can help us identify mental diseases precisely, which is a critical step in diagnosing. Using these systems efficiently can improve the treatment and rapid recovery of patients. We survey different artificial intelligence systems used in mental healthcare, such as mobile applications, machine learning and deep learning methods, and multimodal systems and draw comparisons from recent developments and related challenges. Also, we discuss types of mental disorders and how these different techniques can support the therapist in diagnosing, monitoring, and treating patients with mental disorders.
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人工智能辅助诊断、监测和治疗精神障碍:一项调查
在全球范围内,每 7 人中就有 1 人患有某种精神障碍或药物使用障碍,影响着他们在日常生活中的思维、情感和行为。有精神障碍的人只要得到适当的治疗和支持,就可以继续正常生活。心理健康对身体健康至关重要。近十年来,人工智能在精神健康领域的应用呈指数级增长。然而,由于众多精神疾病的症状相似且常见,但又存在细微差别,因此精神障碍的诊断仍然十分复杂。智能系统可以帮助我们精确识别精神疾病,这是诊断的关键一步。有效利用这些系统可以提高治疗效果,使患者迅速康复。我们调查了用于精神医疗的各种人工智能系统,如移动应用、机器学习和深度学习方法以及多模态系统,并对近期的发展和相关挑战进行了比较。此外,我们还讨论了精神障碍的类型,以及这些不同的技术如何支持治疗师诊断、监控和治疗精神障碍患者。
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