Natural Language Processing in Mental Health Care

Move to the forefront of psychiatric technology with a deep dive into the latest advancements in clinical natural language processing, providing the data-driven precision needed to scale mental health resources effectively. Mental health is one of the most significant public health concerns facing healthcare professionals today. The World Health Organization estimates that every year, 700,000 individuals die by suicide worldwide. With more people experiencing heightened anxiety and mental health pressure, health services are unable to keep up with demand. To deal with ever-increasing mental health problems worldwide, natural language processing proves a vital resource to medical practitioners. This book offers a comprehensive exploration of recent behavior-based natural language processing developments for mental health. It delves into methodologies and aspects of mathematical analysis, covering approaches such as behavioral signal processing in speech and language, speech analysis, clinical natural language processing, and rule-based chatbot approaches. By providing comprehensive coverage, the book equips readers with a deep understanding of the field to keep them abreast of the latest advancements. Readers will find the volume: Explores new and innovative ideas of natural language processing in mental healthcare; Introduces various speech-processing techniques, behavioral detection techniques, and social media detection; Presents various mathematical approaches to the cognitive analysis of mental illness; Uncovers the impact and challenges of using various behavioral NLP techniques. Audience Mental health specialists, academics, AI engineers and data scientists, IT professionals, and business executives exploring significant advancements in digital technologies and how next-generation innovations can enable cognitive and behavioral natural language processing in mental health.