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A Fast and Minimal System to Identify Depression Using Smartphones: Explainable Machine Learning–Based Approach
16 references·1 citing·49 second hopsampled
A Fast and Minimal System to Identify Depression Using Smartphones: Explainable Machine Learning–Based Approach (2023)A Fast and Minimal System to Identify Dep…Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study (2021)Predicting Depression From Sm…Prevalence and Factors Associated with Depression and Anxiety Among First-Year University Students in Bangladesh: A Cross-Sectional Study (2020)Prevalence and Factors Associ…Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations (2020)Artificial Intelligence and S…'I Just Want to Hack Myself to Not Get Distracted' (2020)'I Just Want to Hack Myself t…Tracking Depression Dynamics in College Students Using Mobile Phone and Wearable Sensing (2018)Tracking Depression Dynamics …No More FOMO: Limiting Social Media Decreases Loneliness and Depression (2018)No More FOMO: Limiting Social…Instagram photos reveal predictive markers of depression (2017)Instagram photos reveal predi…Behavior vs. introspection: refining prediction of clinical depression via smartphone sensing data (2016)Behavior vs. introspection: r…Trajectories of depression (2015)Trajectories of depressionMobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study (2015)Mobile Phone Sensor Correlate…Risks of all-cause and suicide mortality in mental disorders: a meta-review (2014)Risks of all-cause and suicid…Contextual experience sampling of mobile application micro-usage (2014)Contextual experience samplin…Measuring Mobile Phone Use: Self-Report Versus Log Data (2013)Measuring Mobile Phone Use: S…The PHQ-8 as a measure of current depression in the general population (2008)The PHQ-8 as a measure of cur…The PHQ-9 (2001)The PHQ-9Nondetection of depression by primary care physicians reconsidered (1995)Nondetection of depression by…Investigating Rhythmicity in App Usage to Predict Depressive Symptoms: Protocol for Personalized Framework Development and Validation Through a Countrywide Study (2024)Investigating Rhythmicity in …Lifetime and 12-Month Prevalence of DSM-III-R Psychiatric Disorders in the United States (1994)Lifetime Prevalence and Age-of-Onset Distributions of DSM-IV Disorders in the National Comorbidity Survey Replication (2005)The WPA- Lancet Psychiatry Commission on the Future of Psychiatry (2017)Facebook language predicts depression in medical records (2018)Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study (2018)Cognitive Structure and Informant Accuracy (1987)Thinking About Answers: The Application of Cognitive Processes to Survey Methodology (1995)Thinking about Answers: The Application of Cognitive Process to Survey Methodology (1996)The Relationship Between Cell Phone Use and Academic Performance in a Sample of U.S. College Students (2015)The Accuracy of Self-Reported Internet Use—A Validation Study Using Client Log Data (2016)Screens, Teens, and Psychological Well-Being: Evidence From Three Time-Use-Diary Studies (2019)Diagnostic and Statistical Manual of Mental Disorders (2013)Diagnostic and Statistical Manual of Mental Disorders (2013)Does Response on the PHQ-9 Depression Questionnaire Predict Subsequent Suicide Attempt or Suicide Death? 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(1980)Happiness is everything, or is it? Explorations on the meaning of psychological well-being. (1989)Gender differences in associations between digital media use and psychological well‐being: Evidence from three large datasets (2020)How Adolescents Use Social Media to Cope with Feelings of Loneliness and Anxiety During COVID-19 Lockdown (2020)Teenagers, screens and social media: a narrative review of reviews and key studies (2020)Mental Health and Behavior of College Students During the Early Phases of the COVID-19 Pandemic: Longitudinal Smartphone and Ecological Momentary Assessment Study (2020)Ecological momentary interventions for mental health: A scoping review (2021)Effects of the COVID-19 lockdown on mental health, wellbeing, sleep, and alcohol use in a UK student sample (2021)
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References

  • 2001The PHQ-944,795 cited
  • 2008The PHQ-8 as a measure of current depression in the general population5,113 cited
  • 2014Risks of all-cause and suicide mortality in mental disorders: a meta-review2,110 cited
  • 2018No More FOMO: Limiting Social Media Decreases Loneliness and Depression946 cited
  • 2015Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study781 cited
  • 2017Instagram photos reveal predictive markers of depression519 cited
  • 2013Measuring Mobile Phone Use: Self-Report Versus Log Data490 cited
  • 2015Trajectories of depression475 cited
  • 2018Tracking Depression Dynamics in College Students Using Mobile Phone and Wearable Sensing339 cited
  • 1995Nondetection of depression by primary care physicians reconsidered319 cited
  • 2020Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations225 cited
  • 2020Prevalence and Factors Associated with Depression and Anxiety Among First-Year University Students in Bangladesh: A Cross-Sectional Study197 cited
  • 2014Contextual experience sampling of mobile application micro-usage160 cited
  • 2021Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study

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143 cited
  • 2016Behavior vs. introspection: refining prediction of clinical depression via smartphone sensing data114 cited
  • 2020'I Just Want to Hack Myself to Not Get Distracted'110 cited
  • Cited by

    • 2024Investigating Rhythmicity in App Usage to Predict Depressive Symptoms: Protocol for Personalized Framework Development and Validation Through a Countrywide Study2 cited