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For Authors
Submit a ProposalNatural Language Processing in Mental Health
One Line Description
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.
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.
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.
Description
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.
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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.
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Author / Editor Details
Sudesh Yadav, PhD is an Assistant Professor at the Govt. College, Ateli, Indira Gandhi University Meerpur, Rewari, Haryana, India. She has published many research papers in international journals and conferences. Her areas of interest include artificial intelligence, IoT, digital image processing, soft computing, and pattern recognition.
Sudesh Yadav, PhD is an Assistant Professor at the Govt. College, Ateli, Indira Gandhi University Meerpur, Rewari, Haryana, India. She has published many research papers in international journals and conferences. Her areas of interest include artificial intelligence, IoT, digital image processing, soft computing, and pattern recognition.
Pethuru Raj Chelliah, PhD is the chief architect in the Edge AI Division of Reliance Jio Platforms Ltd., Bangalore, India. He has published more than thirty research papers in peer-reviewed journals, authored and edited 42 books, and contributed more than 60 book chapters. He focuses on emerging technologies such as the Internet of Things, artificial intelligence model optimization, big and streaming data analytics, blockchain, and digital twins.
Satya Prakash Yadav, PhD is an Associate Professor in the Department of Computer Science and Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, U.P., India, with more than 17 years of experience. He has published four books, two patents, and many research papers in international journals and conferences. His research interests include image processing, information retrieval, feature extraction and digital image processing.
Victor Hugo C. de Albuquerque, PhD is a Professor and Senior Researcher in the Department of Teleinformatics Engineering, Federal University of Ceará, Brazil. He serves as an editor and lead reviewer of several international journals. His interests include pattern recognition, artificial intelligence, image processing and analysis, and automation.
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