Shelly Gupta – författare

Integrating AI in Psychological and Mental Health Care: Techniques, Applications, and Ethical Considerations introduces key concepts and the historical evolution of AI, providing a foundation for understanding its applications in mental health. The content delves into various aspects of AI, including diagnostic tools, machine learning algorithms, and natural language processing, highlighting their roles in enhancing therapeutic outcomes and improving patient care. The discussion encompasses significant mental health conditions such as anxiety, depression, and severe psychological disorders, showcasing how AI technologies can assist in diagnosis, treatment planning, and monitoring. Ethical considerations and privacy issues are critically examined, ensuring a balanced perspective on the benefits and challenges associated with AI-driven interventions. Practical applications, such as virtual psychotherapists and AI-enhanced cognitive behavioral therapy illustrate real-world implementations and their impact on patient care. Additionally, case studies provide insights into successful AI applications in mental health settings, thus enhancing our understanding of potential advantages and obstacles.Covers how artificial intelligence is integrated into psychological and mental health care, including various technologies such as diagnostic tools, machine learning algorithms, and natural language processingIllustrates how AI technologies are being successfully implemented in mental health settings by including real-world examples and case studiesAddresses the ethical implications of using AI in mental health, including privacy concerns and the responsibilities of practitioners

A comprehensive exploration of the intersection between Generative Artificial Intelligence (GAI) and Wireless Sensor Networks (WSNs) , two transformative technologies reshaping data-driven systems. This book examines how generative AI can enhance wireless networks through advanced data analysis, anomaly detection, predictive modeling, and optimization, while also addressing the security risks and ethical challenges of its deployment. Beginning with an overview of GAI and its evolution, the book guides readers through real-world examples, case studies, and frameworks that demonstrate how generative AI can unlock new levels of efficiency and performance in WSNs. Key Features - Examines how Generative AI enhances wireless networks through advanced data analysis, anomaly detection, predictive modeling, and optimization - Demonstrates methods to improve network efficiency, reliability, and adaptability using AI-driven approaches - Addresses critical security risks and ethical challenges linked to the deployment of Generative AI - Explores innovative applications that integrate Generative AI into next-generation wireless systems - Evaluates the impact of AI-driven decision-making on corporate governance and technological adoption - Provides practical insights and case studies illustrating real-world implementations