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Prediction of Depression cases during Covid-19 Pandemic in the United…
Prediction of Depression cases during Covid-19 Pandemic in the United States using machine learning
Title
Prediction of Depression cases during Covid-19 Pandemic in the United States using machine learning
Keywords
Machine Learning
Random Forest
Covid-19
Health Issues
Depression
Project Objective
To predict the factors that causes depression during Covid-19 Pandemic in US.
To evaluate the prediction of machine learning in depression cases.
Project research question
What are the factors that are associated with an increased risk of depression during the COVID-19 pandemic in the US?
How machine learning helps in predicting the depression cases?
Collect and extract documents
Keyword 3
Covid-19
A Novel Work on Analyzing STRESS and Depression level of Indian Population During COVID-19 (2022)
https://dx.doi.org/10.2174/2666255813999201022113918
How do you feel during the COVID‑19 pandemic? A survey using psychological and linguistic self‑report measures and machine learning to investigate m... (2021-06-02)
https://doi.org/10.18725/OPARU-41447
Vulnerability and Protective Factors for PTSD and Depression Symptoms Among Healthcare Workers During COVID-19: A Machine Learning Approach (2022-01-01)
https://doi.org/10.3389/fpsyt.2021.752870
Keyword 4
Health Issues
Pre-pandemic Predictors of Loneliness in Adult Men During COVID-19 (2021-12-01)
https://doi.org/10.3389/fpsyt.2021.775588
Responding to the fear of dying alone during COVID-19 pandemic (2021)
https://dx.doi.org/10.1093/pubmed/fdab135
The Impacts of Prenatal Mental Health Issues on Birth Outcomes during the COVID-19 Pandemic: A Scoping Review (2022-06-01)
https://doi.org/10.3390/ijerph19137670
Keyword 2
Random Forest
Lifestyle predictors of depression and anxiety during COVID-19: a machine learning approach (2022-05-01)
https://doi.org/10.47626/2237-6089-2021-0365
Machine learning techniques for predicting depression and anxiety in pregnant and postpartum women during the COVID-19 pandemic: a cross-sectional regional study (2022)
https://hdl.handle.net/20.500.12713/3220
Machine learning techniques for predicting depression and anxiety in pregnant and postpartum women during the COVID-19 pandemic: a cross-sectional regional study [version 1; peer review: 2 approved] (2022-04-01)
https://doi.org/10.12688/f1000research.110090.1
Keyword 1
Machine Learnng
Machine Learning-Based Prediction Models for Depression Symptoms Among Chinese Healthcare Workers During the Early COVID-19 Outbreak in 2020: A Cros... (2022-04-01)
https://doi.org/10.3389/fpsyt.2022.876995
Prevalence, increase and predictors of family violence during the COVID-19 pandemic, using modern machine learning approaches (2022-08-01))
https://doi.org/10.3389/fpsyt.2022.883294
Viability study of machine learning-based prediction of COVID-19 pandemic impact in obsessive-compulsive disorder patients (2022-02-10)
http://hdl.handle.net/10773/33310
Keyword 5
Depression
Predicting Psychological Distress During the COVID-19 Pandemic: Do Socioeconomic Factors Matter? (2022)
https://dx.doi.org/10.25384/sage.c.5867653
Sentiment Analysis of the COVID-related r/Depression Posts (2021)
https://dx.doi.org/10.48550/arxiv.2108.06215
An Estimate of the Incidence of Depression in Idiopathic Parkinson's Disease (1992)
https://doi.org/10.7916/D80K3N37
Select relevant document
Predicting Psychological Distress During the COVID-19 Pandemic: Do Socioeconomic Factors Matter? (2022)
https://dx.doi.org/10.1177/08944393211069622
DepreST-CAT ; Retrospective Smartphone Call and Text Logs Collected during the COVID-19 Pandemic to Screen for Mental Illnesses (2022)
https://dx.doi.org/10.1145/3534596
Depression and Anxiety on Twitter During the COVID-19 Stay-At-Home Period in 7 Major U.S. Cities (2023-03-01)
https://doi.org/10.1016/j.focus.2022.100062