Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach provides a comprehensive guide for public health authorities, researchers and health professionals in psychological health. The book takes a unique approach by exploring how Artificial Intelligence (AI) and Machine Learning (ML) based solutions can assist with monitoring, detection and intervention for mental health at an early stage. Chapters include computational approaches, computational models, machine learning based anxiety and depression detection and artificial intelligence detection of…mehr
Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach provides a comprehensive guide for public health authorities, researchers and health professionals in psychological health. The book takes a unique approach by exploring how Artificial Intelligence (AI) and Machine Learning (ML) based solutions can assist with monitoring, detection and intervention for mental health at an early stage. Chapters include computational approaches, computational models, machine learning based anxiety and depression detection and artificial intelligence detection of mental health.
With the increase in number of natural disasters and the ongoing pandemic, people are experiencing uncertainty, leading to fear, anxiety and depression, hence this is a timely resource on the latest updates in the field.
Die Herstellerinformationen sind derzeit nicht verfügbar.
Autorenporträt
Shikha Jain is presently working with Jaypee Institute of Information Technology (JIIT), NOIDA, INDIA as Assistant Professor. She has more than seventeen years of research and academic experience. She has received her PhD in computer science from Jaypee Institute of Information Technology, Noida, India. She has published a number of research papers in the renowned journals and conferences. She was advisory board member of a book entitled "Nature-Inspired Algorithms for Big Data Frameworks?, IGI Global. She was a guest editor of a special issue "Advances in Computational Intelligence and its applications? in International Journal of Information Retrieval Research (Publishing phase). She is active reviewer of many International Journals and technical program committee member of various International Conferences. Her research area includes Affective Computing, Emotion Modelling, Cognitive Affective Architectures, Machine Learning and Soft Computing. She is a senior member of IEEE.Dr. Princi Jain is an Associate Professor at Atal Bihari Vajpayee Institute of Medical Sciences (ABVIMS), Lohia Hospital, Delhi, India. She has obtained MD (Internal Medicine) from Vardhman Mahavir Medical College & Safdarjang Hospital, Delhi. She has more than eight years of academic and research experience. She is an active member of Association of Physicians of India and American College of Physicians. She has published a number of research papers in renowned journals and conferences
Inhaltsangabe
1. Mental Health impact of COVID-19 and Machine Learning Applications in Combating Mental Disorders: A Review 2. Multimodal Depression Detection using Machine Learning 3. A Graph Convolutional Networks based Framework for Mental Stress Prediction 4. Women Working in Healthcare Sector during COVID-19 in the National Capital Region of India: A Case Study 5. Impact of Covid19 on Women Educator 6. A Deep Learning approach towards Prediction of Mental Health of Indian's Higher Education Students in Online mode of Teaching and Learning during Pandemic 7. Machine Learning based Analysis and Prediction of College Students' Mental Health during COVID-19 in India. 8. Modeling the Impact of the COVID-19 Pandemic and Socio-economic Factors on Global Mobility and Its Effects on Mental Health 9. Depression Detection: Approaches, Challenges and Future Directions 10. Improving Mental Health Surveillance Over Twitter Text Classification Using Word Embedding Techniques 11. Predicting Loneliness from Social Media text using Machine Learning Techniques 12. Perceiving the Level of Depression from Web Text Using Deep Learning 13. Technologies for Vaccinating COVID-19, Its Variants and Future Pandemics: A Short Survey 14. A Blockchain Approach on Security of Health Records for Children Suffering from Dyslexia during Pandemic Covid -19.
1. Mental Health impact of COVID-19 and Machine Learning Applications in Combating Mental Disorders: A Review 2. Multimodal Depression Detection using Machine Learning 3. A Graph Convolutional Networks based Framework for Mental Stress Prediction 4. Women Working in Healthcare Sector during COVID-19 in the National Capital Region of India: A Case Study 5. Impact of Covid19 on Women Educator 6. A Deep Learning approach towards Prediction of Mental Health of Indian's Higher Education Students in Online mode of Teaching and Learning during Pandemic 7. Machine Learning based Analysis and Prediction of College Students' Mental Health during COVID-19 in India. 8. Modeling the Impact of the COVID-19 Pandemic and Socio-economic Factors on Global Mobility and Its Effects on Mental Health 9. Depression Detection: Approaches, Challenges and Future Directions 10. Improving Mental Health Surveillance Over Twitter Text Classification Using Word Embedding Techniques 11. Predicting Loneliness from Social Media text using Machine Learning Techniques 12. Perceiving the Level of Depression from Web Text Using Deep Learning 13. Technologies for Vaccinating COVID-19, Its Variants and Future Pandemics: A Short Survey 14. A Blockchain Approach on Security of Health Records for Children Suffering from Dyslexia during Pandemic Covid -19.
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Internetauftritt der buecher.de internetstores GmbH
Geschäftsführung: Monica Sawhney | Roland Kölbl | Günter Hilger
Sitz der Gesellschaft: Batheyer Straße 115 - 117, 58099 Hagen
Postanschrift: Bürgermeister-Wegele-Str. 12, 86167 Augsburg
Amtsgericht Hagen HRB 13257
Steuernummer: 321/5800/1497
USt-IdNr: DE450055826
