Artificial Intelligence, Machine Learning, and Mental Health in Pandemics

Artificial Intelligence, Machine Learning, and Mental Health in Pandemics

A Computational Approach

Seng, Kah Phooi; Jain, Princi; Jain, Shikha; Pandey, Kavita

Elsevier Science & Technology

04/2022

418

Mole

Inglês

9780323911962

15 a 20 dias

680

Descrição não disponível.
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.
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Anxiety; Artificial intelligence; BIG data; BiLSTM; Blockchain; Children; Classification; Clustering; CNN; Computational modeling; COVID-19; COVID-19 pandemic; COVID19; Deep learning; Depression; Depression detection; Depression recognition; Distribution; Drones; GloVe; Graph convolutional networks; GRU; Healthcare 4.0; Healthcare sector; Higher education sector; IIoT; Industry 4.0; IoMT; IoT; Lockdown; Loneliness; Machine Learning; Machine learning; Mental disorder; Mental health; Mental health analysis; Node classification; Online learning; Online learning and teaching; Online teaching; Pandemic; Parallel and distributed computing; Psychological health; Smart healthcare system (SHS); Solitude; Stress; Stress prediction; Suicide; Surveillance; SVM; Teachers; Text; Twitter; Twitter data analysis; UAVs; Vaccination; Women; Word embedding; Word2Vec; Working women