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Damien Lekkas

Showing results (1-10 of 39) with videos related to

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Scientific Reports|August 21, 2024
Breaking the silence: leveraging social interaction data to identify high-risk suicide users online using network analysis and machine learningDamien Lekkas, Nicholas C Jacobson
Autonomic Neuroscience : Basic & Clinical|May 25, 2019
The circadian clock control of adipose tissue physiology and metabolismDamien Lekkas, Georgios K Paschos
Scientific Reports|May 14, 2021
Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood traumaDamien Lekkas, Nicholas C Jacobson
Digital Health|November 6, 2023
The hidden depths of suicidal discourse: Network analysis and natural language processing unmask uncensored expressionDamien Lekkas, Nicholas C Jacobson
Computers in Human Behavior|November 15, 2021
Using Smartphone App Use and Lagged-Ensemble Machine Learning for the Prediction of Work Fatigue and BoredomDamien Lekkas, George D Price, Nicholas C Jacobson
European Eating Disorders Review : the Journal of the Eating Disorders Association|August 25, 2022
A machine learning investigation into the temporal dynamics of physical activity-mediated emotional regulation in adolescents with anorexia nervosa and healthy controlsDamien Lekkas, Joseph A Gyorda, Nicholas C Jacobson
Journal of Affective Disorders Reports|June 2, 2021
Association of COVID19-induced anosmia and ageusia with depression and suicidal ideationElad Yom-Tov, Damien Lekkas, Nicholas C Jacobson
Internet Interventions|August 17, 2021
Predicting acute suicidal ideation on Instagram using ensemble machine learning modelsDamien Lekkas, Robert J Klein, Nicholas C Jacobson
Digital Biomarkers|October 30, 2024
Detecting Longitudinal Trends between Passively Collected Phone Use and Anxiety among College StudentsJoseph A Gyorda, Damien Lekkas, Nicholas C Jacobson
Journal of Affective Disorders|January 5, 2021
Deep learning paired with wearable passive sensing data predicts deterioration in anxiety disorder symptoms across 17-18 yearsNicholas C Jacobson, Damien Lekkas, Raphael Huang, et al.
Pageof 4

Showing results (1-10 of 39) with videos related to

Sort By:
Pageof 4
Scientific Reports|August 21, 2024
Breaking the silence: leveraging social interaction data to identify high-risk suicide users online using network analysis and machine learningDamien Lekkas, Nicholas C Jacobson
Autonomic Neuroscience : Basic & Clinical|May 25, 2019
The circadian clock control of adipose tissue physiology and metabolismDamien Lekkas, Georgios K Paschos
Scientific Reports|May 14, 2021
Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood traumaDamien Lekkas, Nicholas C Jacobson
Digital Health|November 6, 2023
The hidden depths of suicidal discourse: Network analysis and natural language processing unmask uncensored expressionDamien Lekkas, Nicholas C Jacobson
Computers in Human Behavior|November 15, 2021
Using Smartphone App Use and Lagged-Ensemble Machine Learning for the Prediction of Work Fatigue and BoredomDamien Lekkas, George D Price, Nicholas C Jacobson
European Eating Disorders Review : the Journal of the Eating Disorders Association|August 25, 2022
A machine learning investigation into the temporal dynamics of physical activity-mediated emotional regulation in adolescents with anorexia nervosa and healthy controlsDamien Lekkas, Joseph A Gyorda, Nicholas C Jacobson
Journal of Affective Disorders Reports|June 2, 2021
Association of COVID19-induced anosmia and ageusia with depression and suicidal ideationElad Yom-Tov, Damien Lekkas, Nicholas C Jacobson
Internet Interventions|August 17, 2021
Predicting acute suicidal ideation on Instagram using ensemble machine learning modelsDamien Lekkas, Robert J Klein, Nicholas C Jacobson
Digital Biomarkers|October 30, 2024
Detecting Longitudinal Trends between Passively Collected Phone Use and Anxiety among College StudentsJoseph A Gyorda, Damien Lekkas, Nicholas C Jacobson
Journal of Affective Disorders|January 5, 2021
Deep learning paired with wearable passive sensing data predicts deterioration in anxiety disorder symptoms across 17-18 yearsNicholas C Jacobson, Damien Lekkas, Raphael Huang, et al.
Pageof 4