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International Journal of Environmental Research and Public Health
|
March 6, 2021
Mental Health Outreach via Supportive Text Messages during the COVID-19 Pandemic: Improved Mental Health and Reduced Suicidal Ideation after Six Weeks in Subscribers of Text4Hope Compared to a Control Population
Vincent I O Agyapong, Reham Shalaby, Marianne Hrabok, et al.
Analytical Chemistry
|
December 4, 2023
Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances
Fei Wang, Daniel Pasin, Michael A Skinnider, et al.
Disaster Medicine and Public Health Preparedness
|
February 8, 2021
Text4Hope: Receiving Daily Supportive Text Messages for 3 Months During the COVID-19 Pandemic Reduces Stress, Anxiety, and Depression
Vincent I O Agyapong, Marianne Hrabok, Reham Shalaby, et al.
Scientific Reports
|
October 30, 2021
Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study
Bo Cao, Yang S Liu, Alessandro Selvitella, et al.
JMIR Mental Health
|
December 9, 2020
Changes in Stress, Anxiety, and Depression Levels of Subscribers to a Daily Supportive Text Message Program (Text4Hope) During the COVID-19 Pandemic: Cross-Sectional Survey Study
Vincent Israel Ouoku Agyapong, Marianne Hrabok, Wesley Vuong, et al.
PLOS Digital Health
|
November 7, 2024
Early identification of children with Attention-Deficit/Hyperactivity Disorder (ADHD)
Yang S Liu, Fernanda Talarico, Dan Metes, et al.
Journal of Affective Disorders
|
January 14, 2021
Individualized identification of first-episode bipolar disorder using machine learning and cognitive tests
Jeffrey Sawalha, Liping Cao, Jianshan Chen, et al.
Frontiers in Cardiovascular Medicine
|
December 11, 2020
Neural-Network-Based Diagnosis Using 3-Dimensional Myocardial Architecture and Deformation: Demonstration for the Differentiation of Hypertrophic Cardiomyopathy
Alessandro Satriano, Yarmaghan Afzal, Muhammad Sarim Afzal, et al.
Journal of Pediatric Gastroenterology and Nutrition
|
November 30, 2025
Using machine learning to predict clinical remission with exclusive enteral nutrition in pediatric Crohn disease
Ricardo G Suarez Suarez, Daniel G McClement, Roberto Vega, et al.
Neuroimage. Clinical
|
July 31, 2022
Predicting escitalopram treatment response from pre-treatment and early response resting state fMRI in a multi-site sample: A CAN-BIND-1 report
Jacqueline K Harris, Stefanie Hassel, Andrew D Davis, et al.
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Search research articles
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Showing results (101-110 of 122) with videos related to
Sort By:
Page
of 13
International Journal of Environmental Research and Public Health
|
March 6, 2021
Mental Health Outreach via Supportive Text Messages during the COVID-19 Pandemic: Improved Mental Health and Reduced Suicidal Ideation after Six Weeks in Subscribers of Text4Hope Compared to a Control Population
Vincent I O Agyapong, Reham Shalaby, Marianne Hrabok, et al.
Analytical Chemistry
|
December 4, 2023
Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances
Fei Wang, Daniel Pasin, Michael A Skinnider, et al.
Disaster Medicine and Public Health Preparedness
|
February 8, 2021
Text4Hope: Receiving Daily Supportive Text Messages for 3 Months During the COVID-19 Pandemic Reduces Stress, Anxiety, and Depression
Vincent I O Agyapong, Marianne Hrabok, Reham Shalaby, et al.
Scientific Reports
|
October 30, 2021
Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study
Bo Cao, Yang S Liu, Alessandro Selvitella, et al.
JMIR Mental Health
|
December 9, 2020
Changes in Stress, Anxiety, and Depression Levels of Subscribers to a Daily Supportive Text Message Program (Text4Hope) During the COVID-19 Pandemic: Cross-Sectional Survey Study
Vincent Israel Ouoku Agyapong, Marianne Hrabok, Wesley Vuong, et al.
PLOS Digital Health
|
November 7, 2024
Early identification of children with Attention-Deficit/Hyperactivity Disorder (ADHD)
Yang S Liu, Fernanda Talarico, Dan Metes, et al.
Journal of Affective Disorders
|
January 14, 2021
Individualized identification of first-episode bipolar disorder using machine learning and cognitive tests
Jeffrey Sawalha, Liping Cao, Jianshan Chen, et al.
Frontiers in Cardiovascular Medicine
|
December 11, 2020
Neural-Network-Based Diagnosis Using 3-Dimensional Myocardial Architecture and Deformation: Demonstration for the Differentiation of Hypertrophic Cardiomyopathy
Alessandro Satriano, Yarmaghan Afzal, Muhammad Sarim Afzal, et al.
Journal of Pediatric Gastroenterology and Nutrition
|
November 30, 2025
Using machine learning to predict clinical remission with exclusive enteral nutrition in pediatric Crohn disease
Ricardo G Suarez Suarez, Daniel G McClement, Roberto Vega, et al.
Neuroimage. Clinical
|
July 31, 2022
Predicting escitalopram treatment response from pre-treatment and early response resting state fMRI in a multi-site sample: A CAN-BIND-1 report
Jacqueline K Harris, Stefanie Hassel, Andrew D Davis, et al.
Page
of 13