Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach

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. Examines the datasets and algorithms that can be used to detect mental disorders Covers machine learning solutions that can help determine the precautionary measures of psychological health problems Highlights innovative AI solutions and bi-statistics computation that can strengthen day-to-day medical procedures and decision-making INDICE: 1. Mental Health impact of COVID-19 and Machine Learning Applications in Combating Mental Disorders: A Review2. Multimodal Depression Detection using Machine Learning3. A Graph Convolutional Networks based Framework for Mental Stress Prediction4. Women Working in Healthcare Sector during COVID-19 in the National Capital Region of India: A Case Study5. Impact of Covid19 on Women Educator6. A Deep Learning approach towards Prediction of Mental Health of Indian's Higher Education Students in Online mode of Teaching and Learning during Pandemic7. 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 Health9. Depression Detection: Approaches, Challenges and Future Directions 10. Improving Mental Health Surveillance Over Twitter Text Classification Using Word Embedding Techniques11. Predicting Loneliness from Social Media text using Machine Learning Techniques12. Perceiving the Level of Depression from Web Text Using Deep Learning13. Technologies for Vaccinating COVID-19, Its Variants and Future Pandemics: A Short Survey14. A Blockchain Approach on Security of Health Records for Children Suffering from Dyslexia during Pandemic Covid -19.

• ISBN: 978-0-323-91196-2
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 325
• Fecha Publicación: 01/05/2022
• Nº Volúmenes: 1
• Idioma: Inglés