论文标题
使用深度学习和转移学习对社交媒体文本进行精神疾病分类
Mental Illness Classification on Social Media Texts using Deep Learning and Transfer Learning
论文作者
论文摘要
鉴于当前全球的社会距离限制,大多数人现在都使用社交媒体作为他们的主要交流媒介。因此,数百万患有精神疾病的人被隔离了,他们无法亲自获得帮助。他们更依赖在线场所来表达自己,并寻求有关处理精神障碍的建议。根据世界卫生组织(WHO)的数据,大约有4.5亿人受到影响。精神疾病(例如抑郁,焦虑等)非常普遍,并影响了个体的身体健康。最近提出了人工智能(AI)方法,以帮助精神卫生提供者,包括精神科医生和心理学家,基于患者的真实信息(例如,医疗记录,行为数据,社交媒体利用等)的决策。 AI创新表明,在从计算机愿景到医疗保健的众多现实应用应用程序中,主要执行。这项研究分析了REDDIT平台上的非结构化用户数据,并分类了五种常见的精神疾病:抑郁,焦虑,躁郁症,ADHD和PTSD。我们训练了传统的机器学习,深度学习和转移学习多级模型,以检测个人的精神障碍。这项工作将通过自动化检测过程并告知适当当局需要紧急援助的人,从而使公共卫生系统受益。
Given the current social distance restrictions across the world, most individuals now use social media as their major medium of communication. Millions of people suffering from mental diseases have been isolated due to this, and they are unable to get help in person. They have become more reliant on online venues to express themselves and seek advice on dealing with their mental disorders. According to the World health organization (WHO), approximately 450 million people are affected. Mental illnesses, such as depression, anxiety, etc., are immensely common and have affected an individuals' physical health. Recently Artificial Intelligence (AI) methods have been presented to help mental health providers, including psychiatrists and psychologists, in decision making based on patients' authentic information (e.g., medical records, behavioral data, social media utilization, etc.). AI innovations have demonstrated predominant execution in numerous real-world applications broadening from computer vision to healthcare. This study analyzes unstructured user data on the Reddit platform and classifies five common mental illnesses: depression, anxiety, bipolar disorder, ADHD, and PTSD. We trained traditional machine learning, deep learning, and transfer learning multi-class models to detect mental disorders of individuals. This effort will benefit the public health system by automating the detection process and informing appropriate authorities about people who require emergency assistance.