Data Science Applications of Post-COVID-19 Psychological Disorders isbn:9798886971651

The COVID-19 epidemic has thrown the globe into chaos as governments struggle to contain the virus's spread. While considerable attention has been paid to health problems, reports of the social-psychological impacts of this pandemic are on the increase, ranging from mental distress and personal disputes to racial assaults and patriotic behaviors. Moreover, these social-psychological impacts may have long-term repercussions that will likely outlast the epidemic. Globally, the physical impacts of COVID-19 may be felt. The influence of Post-COVID-19 on mental health is a subject that has not been well explored. The reaction to the Covid-19 pandemic may resemble the response to natural catastrophes or other comparable catastrophic occurrences affecting a community and may create chronic anguish in the afflicted population. The psychological reaction to the Covid-19 epidemic has been immediately recorded; in communities rarely affected, it resembles symptoms of post-traumatic stress disorder (PTSD). The unfavorable psychological effects of COVID-19, such as anxiety and depression, have been widely expected but have not yet been precisely quantified. Data science enables academics to evaluate the past and future consequences of mental diseases on the United States and worldwide populations. Contents Preface Abstract Definitions About the Pandemic Psychological Impacts Structure of the Book Chapter 1 Post-COVID-19 Mental Disorder and Its Consequences Abstract Introduction Background Usage of Data Science in Healthcare Systems Applications Post COVID Complications and Their Consequences Post COVID-19 Psychological Impacts Consequences Perplexity or Strange Attitude Sleep Disorder Addiction to Substances Self-Destructive Attitude Anxiousness Mood Swings or Depression Post-COVID Stress Disorder A Poor Understanding of Contagion Subconscious Social Problems False News Inflexibility Security of Family Discussion Conclusion References Chapter 2 Contemplating the Post-COVID Psychological Disorders in a Selective Sample Using DASS-21 and the WHO-5 Well-Being Index Abstract Introduction Analytical Framework Literature Review Methods Questionnaire Tool DASS-21 - Survey in Malaysia A Survey Conducted in Tamil Nadu in DASS 21 and WHO-5 Well-Being Indexes Results and Analysis WHO-5 Well-Being Index DASS-21 Conclusion References Chapter 3 Data Science Applications of Post-COVID-19 Mental Illness Abstract Introduction Background Related Works Data Science Application of Post-COVID 19 Mental Illness Diagnosis Depression Applications Healthcare Industry Data Science in Psychiatry Crises Text Line Ellie, the 3-D Chat Bot Quartet Health COVIDiSTRESS Risks in Education Sector E-Commerce Industry Image Processing and Computer Vision Predictive Analytics in Psychological Effects Developing Drugs Genomics Data Science Remote Supervision Discussion Conclusion Future Enhancement References Chapter 4 Prediction of Mental Distress about COVID-19 among Higher Education Students in Odisha, India Abstract Introduction Related Work Proposed Methodology Result Analysis Conclusion Future Work Acknowledgments References Chapter 5 Impact of Post-COVID Syndrome in Hospitalized Patients Abstract Introduction Causes of Post-COVID Syndrome Objectives Motivation Background Related Works Post-COVID Conditions Multi-Organ Effects of COVID-19 Effects of COVID-19 Hospitalization Novel Symptoms Design Procedure Materials and Methods Statistical Analysis Predicts of the Post-COVID-19 Symptoms Discussion Conclusion Future Enhancement References Biographical Sketch Chapter 6 Computational Intelligence Models for Stress Abstract Introduction What Does Stress Mean? Definition of Stress Hormones of Stress Different Types of Stress Acute Stress Episodic Acute Stress Chronic Stress Workplace Stress Stress Management Recognize the Source of Stress Identify the Sources of Our Stress Develop the Ability to Recognize and Respond to Stress Signals Recognize the Stress Management Work Techniques Use Stress-Reduction Practices That Are Both Healthy and Effective Make Self-Care a Priority Seek Assistance Techniques and Strategies for Stress Management Action-Oriented Approaches Be Self-Confident Reduce the Amount of Noise Keep Track of Our Time Establishing Limits Get Our Heads Out of Our Asses Emotion–Oriented Approaches Visualizations and Affirmations Cognitive Restructuring The ABC Method Acceptance-Oriented Methodologies Exercise and Diet Physical and Mental Relaxation through Meditation Develop Resiliency Discuss It Get Some Rest Stress Management in the Workplace Employment, Earnings, and Technical Innovation: A Relationship Artificial Intelligence in the Environment Artificial Intelligence Role in Stress Management Automated Technologies for Mental Health Automation Employees Can Benefit From AI Human Error Risks are Reduced Stress Sensors and Emotion Recognition Artificial Intelligence (AI) Chatbots Rendering Repeated Work Moot Ability to Work More Independently Improved Workflow Management Potential Power of Integrated Digital Tools Challenges References Chapter 7 Multimodality Analysis of Psychological Disorders Abstract Introduction Psychological Disorders Neurodevelopmental Disorders Bipolar and Affiliated Disorders Anxiety Disorders Stress-Related Disorders Dissociative Disorders Physical Symptom Disorders Eating Disorders Sleep Disorders Disruptive Disorders Review on Multimodality Analysis of Psychological Disorders About Psychological Disorders Machine Learning Model Training Types of Models Supervised Learning Unsupervised Learning Semi-Supervised Learning Transfer Learning Reinforcement Learning Research Challenges in Multimodality Analysis of Psychological Disorders Data Labeling Inter-User Friction Intra-User Friction Detector Data Emulsion Integration with Other Systems Clinical Confirmation Conclusion References Chapter 8 Mathematical Modeling and Analysis of Psychological Disorders Abstract Introduction Classification of Psychological Disorder COVID-19 Impact on Mental Health Mathematical Modeling Techniques to Determine the Post-COVID-19 Effect and Its Spread Related Works Conclusion References Chapter 9 Impact of Post-COVID-19 on the Elderly-Emotional Stress and Effects: A Data Science Approach Abstract Introduction Background Related Works About Elder People Emotional Stress Tiredness and Mood Swings Methodology and Implementation Analysis Discussion Conclusion Future Work References Chapter 10 Work from Home-Related Depression Analysis Abstract Introduction The Benefits and Drawbacks of Working from Home Literature Review Methodology A Single Occurrence or Temporary Circumstances May Cause Types of Stress Depression and the Effects of Stress Mindfulness and Yoga Results and Discussion Conclusion References Chapter 11 The Effect of Psychological Disorders on Students’ Academic Performance Abstract Introduction Background Related Works Pandemic’s Affect on Education Methodology Implementation Analysis Dataset Description Experiment Results and Analysis Evaluating Multiple-Choice Questionnaires Descriptive Statistics Results The Outcomes of Models’ Effectiveness Discussion Conclusion Future Enhancement References Chapter 12 Psychological Resilience: A Conceptual Framework Abstract Introduction Psychological Disorders Psychological Resilience Literature Review Methodology and Framework Conclusion References Chapter 13 Challenges and Privacy Concerns Related to Mental Health Abstract Introduction Psychological Impacts of Social Distancing Curbs Mental Health Issues after COVID-19 Recovery Psychological Impacts on Frontline Healthcare Professionals Interruptions to Critical Services of Mental Healthcare Social Inequalities and Decline in Psychological Healthcare Post COVID-19 Mental Health Information System Access and Management Security Challenges of MHIS Existing Privacy-Preserving Mechanisms Privacy Preservation of the Encrypted Dataset Using K-Anonymization Conclusion References Chapter 14 Post-COVID Impact on Skin Allergies Abstract Introduction Motivation Objectives Scope Benefits Background Related Works About Skin Allergies after Recovering from COVID-19 Maculopapular Eruptions COVID Toes Hives Water Blisters Livedo MIS-C Methodology and Framework Data Set Feature Extraction Logistic Regression Decision Tree (DT) Support Vector Machines (SVM) K-Nearest Neighbors (KNN) Gaussian Naïve Bias Gradient Boosting XGB Stochastic Gradient Boosting Performance Metrics Implementation Analysis Feature Selection Module Classification Module Logistic Regression Decision Tree Gaussian NB Neighbors Classifier Random Forest Classifier SVM Gradient Boosting Classifier XGB Classifier SGD Classifier Discussion Conclusion Future Enhancement References About the Editor Index Blank Page Blank Page