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.
Table of Contents:
Preface xv
Part 1: Foundations of NLP in Mental Health 1
1 Introduction to NLP in Mental Health 3
Anandaraj S.P., Rakesh Mohanty, Trapty Agarwal, Taskeen Zaidi and Pratyashi Satapathy
2 Mental Health Issues, Concerns, and Solutions 15
Y. Narasimha Raja, Suvendu Narayan Mishra, Shweta Bajaj and M. N. Nachappa
3 AI Technologies, Tools, and Industrial Use Cases 27
Kalpana K. Harish, Sasanka Choudhury, Awakash Mishra and Haripriya V.
4 NLP Techniques, Tools, and Use Cases of Speech Tagging 39
Kuppala Saritha, Prabhat Kumar Sahu, Trapty Agarwal and Ganesh D.
Part 2: AI and Machine Learning for Behavioral Understanding 53
5 Classification and Regression Algorithms in Behavioral NLP 55
Selvaraj Poornima, Manoranjan Parhi, Smita Mishra and Raghavendra R.
6 Deep Learning Algorithms for Behavioral Understanding of Mental Health 69
Balamurugan S., M. Chandra Sekhar, Jitendriya Biswal, Savita and Sarbeswar Hota
7 Mental Health Detection Using Natural Language Processing 85
Murugan R., Syed Siraj Ahmed, Snehanshu Dey, Shweta Bajaj and Bichitrananda Patra
8 Behavioral Signal Processing 103
Rengarajan A., Raghavendra T. S., Praveen Priyaranjan Nayak and Trapty Agarwal
9 Prediction of Suicidal Thoughts and Pychiatric Symptoms 119
Manju Bargavi S. K., Y. Narasimha Raja, Surjeet Sahoo and Trapty Agarwal
Part 3: Advanced Methods and Evaluation Techniques 135
10 Evaluation of Model Performance—Confusion Matrices, Sensitivity, Specificity, Kappa Statistics, Precision, Recall F-Measure, ROC Curve, Etc. 137
Kamalraj R., Akkamahadevi C., Duryodhan Jena and Aditya Yadav
11 Methods of Pruning and Tagging 151
Awakash Mishra, Gobi N., Pallavi M. and Avinash Samantra
12 Social Media for Depression Detection in Mental Health 165
Smita Mishra, Febin Prakash, Rosan Basha and Chinmaya Kumar Mohapatra
13 Creation of Cognitive Behavioral Chatbots for Mental Health 181
Monika Joshi, Pushpa J., Sharon M. and Manoranjan Dash
Part 4: Future Directions in Behavioral NLP 195
14 The Future of Behavioral Natural Language Processing in Healthcare 197
Monika Joshi, Nanthini K., Devi S. and Biswaranjan Swain
15 Medical Graph RAG: Toward Safe Medical Large Language Model via Graph Retrieval-Augmented Generation 215
Trapty Agarwal, Ramkumar Krishnamoorthy, Praveena K. N., Adya Kinkar Panda and Ayasa Kanta Mohanty
16 Real-Time Cognitive Load Prediction in Digital Environments 233
Monika Joshi, Pushpa J., Sharon M. and Manoranjan Dash
17 NLP-Based Gamification Approaches for Personalized Mental Wellness Support 251
Samir Sahu, Trapty Agarwal, Sanjeev Kumar Mandal, Deepthi S. and Tapasmini Sahoo
18 Context-Aware NLP for Early Detection of Cognitive and Emotional Distress 269
Chandan Das, Awakash Mishra, Preethi D. and Mohammed Mujeerulla
19 Deep Learning Techniques for Analyzing Mood Variability in Patients 285
Pritam Keshari Sahoo, Awakash Mishra, Suneetha K., Smitha S. P. and Laxmidhar Maharana
20 Text-Based Cognitive Bias Identification for Assessing Negative Thinking Patterns 303
Jyoti Ranjan Das, Savita, Kannagi Anbazhagan and Sridevi S.
References 316
Index 319
About the Author :
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, 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.
