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    1. Psykologi och pedagogik
    2. Psykologi
    3. Psykologisk metod

    Artificial Intelligence For Detecting Mental Disorders

    Concepts and Methodologies

    AvAbdul Mueed Hafiz,Mohammad Ahsan Chishti

    Inbunden, Engelska, 2026

    1 660 kr

    Kommande

    Beskrivning

    Mental disorders can affect the ability of an individual to relate to others and function normally. While there are many different types of mental disorders, some common ones include anxiety disorders like panic, obsessive-compulsive disorder, phobias, depression, bipolar disorder, eating disorders, personality disorders, post-traumatic stress disorder, and psychotic disorders including schizophrenia. Mental disorders are common with around 1 billion people globally currently living with a mental disorder. When considering ever having a disorder in life, broad research suggests roughly 30% people worldwide will experience one at some point.In view of this silent epidemic, it is imperative to come up with state-of-the-art techniques including AI to stem it. By addressing the new frontiers of AI in medical applications, this insightful book provides knowledge and the associated wisdom to researchers. Since the subject is relatively unexplored, there is a good opportunity for researchers to form a platform to pitch their ideas for the goal of AI-based problem solving. The methodologies involved include developing robust and accurate disorder prediction technologies, and even disorder management technologies, from body-state data, and body-signal data like MRI, EEG, ECG, polygraph test data, history, prescriptions, etc.

    Produktinformation

    • Utgivningsdatum:2026-11-17
    • Mått:156 x 234 x undefined mm
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:238
    • Förlag:Taylor & Francis Ltd
    • ISBN:9781032856018

    Utforska kategorier

    • Psykologisk metod inom Psykologi och pedagogik
    • Specialundervisning inom Psykologi och pedagogik
    • Alzheimer, demens inom Medicin

    Mer om författaren

    Abdul Mueed Hafiz completed his B.Tech in Electronics & Communication Engineering in 2005 from the National Institute of Technology Srinagar, India; his M. Tech in Communication & Information Technology in 2008 from the National Institute of Technology Srinagar; and his PhD in Computer Vision in 2018 from the University of Kashmir, Srinagar, India. Currently, he is Senior Assistant Professor at the Department of Electronics & Communication Engineering, Institute of Technology, University of Kashmir. He has also served twice as Head of the Department. He has publications in international journals, conferences and book chapters. He serves as a reviewer for reputed journals in IEEE, Springer, Elsevier, etc. He is also a member of the ACM Society. His research interests include Neural networks, Learning systems, Computer vision and Quantum machine learning. Mohammad Ahsan Chishti has done his Ph.D. from National Institute of Technology Srinagar. He has completed Bachelor of Engineering and M.S. in Computer and Information Engineering from International Islamic University Malaysia. Presently he is working as Associate Professor in the Department Computer Science & Engineering and Associate Dean (Research & Consultancy) at National Institute of Technology Srinagar. He has more than 160 research publications to his credit and 17 patents. He has successfully completed a number of sponsored research projects. He has been awarded “IEI Young Engineers Award 2015-2016” by the Institution of Engineers (India) and “Young Scientist Award 2009-2010” from Department of Science & Technology, Government of Jammu and Kashmir. He has guided 10 research scholars for the award of Ph.D. in Engineering and his research area includes Artificial Intelligence, Machine Learning, Internet of Things and Digital Twins.

    Innehållsförteckning

    • Preface. 1. Artificial Intelligence in the World of Mental Health. 2. AI-Driven Insights and Implications of Cognitive Load in Mental Health. 3. AI-Powered Mental Health Digital Twins: Integrating Behavioral, Physiological, and Environmental Data for Precision Psychiatry. 4. Exploring Higher-Order Gene Interactions in Mental Health Using Hyper Network Models. 5. AI-Powered Mental Health Monitoring System Using Multimodal Data. 6. Explainable Semantic AI Framework for Multimodal Diagnosis of Psychiatric Disorders. 7. AI and PTSD: Understanding, Addressing, and Overcoming the Challenges. 8. CNN-Based Detection of Schizophrenia using EEG Data. 9. Early Detection of Brain Stroke using Deep Learning: A Review. 10. Advancing Mental Health Monitoring: Harnessing Artificial Intelligence in Wearable Devices for Predicting Anxiety and Depression.