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Predicting Symptom Trajectories of Schizophrenia using Mobile Sensing
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Validation and Utility of a Self-report Version of PRIME-MD The PHQ Primary Care Study
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Extending the simple linear regression model to account for correlated responses: An introduction to generalized estimating equations and multi-level mixed modelling
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An overview of methods for the analysis of longitudinal data
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Early response or nonresponse at week 2 and week 3 predict ultimate response or nonresponse in adolescents with schizophrenia treated with olanzapine: results from a 6-week randomized, placebo-controlled trial
inferredcites →https://doi.org/10.1016/0006-3223(93)90307-yopenalex-snapshot
Lateralized attentional abnormality in schizophrenia is correlated with severity of symptoms
inferredcites →https://doi.org/10.1016/0197-2456(81)90056-8openalex-snapshot
A method for assessing the quality of a randomized control trial
inferredcites →https://doi.org/10.1016/0920-9964(95)00068-2openalex-snapshot
Substance use: a powerful predictor of relapse in schizophrenia
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Prediction of Relapse After Cognitive-Behavioral Treatment of Gambling Disorder in Individuals With Chronic Schizophrenia: A Survival Analysis
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Classification of bipolar disorder episodes based on analysis of voice and motor activity of patients
inferredcites →https://doi.org/10.1016/j.ypsy.2012.08.085openalex-snapshot
Incarceration Among Adults Who Are in the Public Mental Health System: Rates, Risk Factors, and Short-Term Outcomes
inferredcites →https://doi.org/10.1016/s0924-9338(15)30442-9openalex-snapshot
Utilizing Smartphones as an Effective Way to Support Patients with Bipolar Disorder: Results of the Monarca Study
inferredcites →https://doi.org/10.1017/s0033291700024247openalex-snapshot
Predicting relapse in schizophrenia: the development and implementation of an early signs monitoring system using patients and families as observers, a preliminary investigation
inferredcites →https://doi.org/10.1037/prj0000243openalex-snapshot
CrossCheck: Integrating self-report, behavioral sensing, and smartphone use to identify digital indicators of psychotic relapse.
inferredcites →https://doi.org/10.1093/biomet/73.1.13openalex-snapshot
Longitudinal Data Analysis Using Generalized Linear Models
inferredcites →https://doi.org/10.1093/jamia/ocv200openalex-snapshot
Automatic detection of social rhythms in bipolar disorder
inferredcites →https://doi.org/10.1093/schbul/sbn167openalex-snapshot
Periods of Recovery in Deficit Syndrome Schizophrenia: A 20-Year Multi-follow-up Longitudinal Study
inferredcites →https://doi.org/10.1093/schbul/sbr171openalex-snapshot
Comparing Retrospective Reports to Real-Time/Real-Place Mobile Assessments in Individuals With Schizophrenia and a Nonclinical Comparison Group
inferredcites →https://doi.org/10.1093/schbul/sbw006openalex-snapshot
Paranoid Ideation and Violence: Meta-analysis of Individual Subject Data of 7 Population Surveys
inferredcites →https://doi.org/10.1109/acii.2013.117openalex-snapshot
Stress Recognition Using Wearable Sensors and Mobile Phones
inferredcites →https://doi.org/10.1109/icassp.2007.367201openalex-snapshot
Capturing Spontaneous Conversation and Social Dynamics: A Privacy-Sensitive Data Collection Effort
inferredcites →https://doi.org/10.1109/jstsp.2016.2565381openalex-snapshot
Leveraging Multi-Modal Sensing for Mobile Health: A Case Review in Chronic Pain
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A survey of mobile phone sensing
inferredcites →https://doi.org/10.1109/mobihealth.2014.7015923openalex-snapshot
Correlation of significant places with self-reported state of bipolar disorder patients
inferredcites →https://doi.org/10.1109/mprv.2015.54openalex-snapshot
Smartphones in Mental Health: Detecting Depressive and Manic Episodes
inferredcites →https://doi.org/10.1109/percomw.2012.6197525openalex-snapshot
Can smartphones detect stress-related changes in the behaviour of individuals?
inferredcites →https://doi.org/10.1109/wh.2016.7764553openalex-snapshot
Behavior vs. introspection: refining prediction of clinical depression via smartphone sensing data
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A working guide to boosted regression trees
inferredcites →https://doi.org/10.1145/2030112.2030164openalex-snapshot
Passive and In-Situ assessment of mental and physical well-being using mobile sensors
inferredcites →https://doi.org/10.1145/2536853.2536882openalex-snapshot
Monitoring activity of patients with bipolar disorder using smart phones
inferredcites →https://doi.org/10.1145/2647868.2654933openalex-snapshot
Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits
inferredcites →https://doi.org/10.1145/2750858.2807537openalex-snapshot
Visualization of time-series sensor data to inform the design of just-in-time adaptive stress interventions
inferredcites →https://doi.org/10.1145/2968219.2968299openalex-snapshot
Towards multi-modal anticipatory monitoring of depressive states through the analysis of human-smartphone interaction
inferredcites →https://doi.org/10.1145/2968219.2968305openalex-snapshot
Large scale mood and stress self-assessments on a smartwatch
inferredcites →https://doi.org/10.1145/2968219.2968306openalex-snapshot
Continuous stress detection using a wrist device
inferredcites →https://doi.org/10.1159/000111551openalex-snapshot
Consistency of Brief Psychiatric Rating Scale Factor Structure across a Broad Spectrum of Schizophrenia Patients
inferredcites →https://doi.org/10.1176/ajp.148.2.224openalex-snapshot
Drug abuse in schizophrenic patients: clinical correlates and reasons for use
inferredcites →https://doi.org/10.1176/appi.ps.201000505openalex-snapshot
Incarceration Among Adults Who Are in the Public Mental Health System: Rates, Risk Factors, and Short-Term Outcomes
inferredcites →https://doi.org/10.1176/appi.ps.201500130openalex-snapshot
Mobile Behavioral Sensing for Outpatients and Inpatients With Schizophrenia
inferredcites →https://doi.org/10.1177/1359786810385490openalex-snapshot
Review: Suicide and schizophrenia: a systematic review of rates and risk factors
inferredcites →https://doi.org/10.1214/aoms/1177703732openalex-snapshot
Robust Estimation of a Location Parameter
inferredcites →https://doi.org/10.1214/aos/1013203451openalex-snapshot
Greedy function approximation: A gradient boosting machine.
inferredcites →https://doi.org/10.1371/journal.pone.0145533openalex-snapshot
Psychotic-Like Experiences and Nonsuidical Self-Injury in England: Results from a National Survey
inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.21437/interspeech.2007-256openalex-snapshot
Conversation detection and speaker segmentation in privacy-sensitive situated speech data
inferredcites →https://doi.org/10.2196/jmir.4273openalex-snapshot
Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study
inferredcites →https://doi.org/10.2466/pr0.1962.10.3.799openalex-snapshot
The Brief Psychiatric Rating Scale
inferredcites →https://doi.org/10.3928/0048-5713-20020901-06openalex-snapshot
The PHQ-9: A New Depression Diagnostic and Severity Measure
inferredcites →https://doi.org/10.4108/icst.mobihealth.2014.257423openalex-snapshot
Correlation of significant places with self-reported state of bipolar disorder patients
inferredcites →https://doi.org/10.4108/icst.pervasivehealth.2011.246161openalex-snapshot
BeWell: A Smartphone Application to Monitor, Model and Promote Wellbeing
inferredcites →https://doi.org/10.4108/icst.pervasivehealth.2013.252148openalex-snapshot
Unobtrusive Sleep Monitoring using Smartphones
inferredcites →https://doi.org/10.4324/9781410605542-11openalex-snapshot
Analysis of Longitudinal Data
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.5281/zenodo.19712698openalex-snapshot
A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
inferredcites →https://doi.org/10.5555/1953048.2078195openalex-snapshot
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.7717/peerj.2537openalex-snapshot
The relationship between mobile phone location sensor data and depressive symptom severity
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4103311openalex-extracted
Smartphone-Based Mobility Metrics Capture Daily Social Motivation and Behavior in Schizophrenia
inferred← citeshttps://doi.org/10.1002/per.2262openalex-snapshot
Investigating the Relationships between Mobility Behaviours and Indicators of Subjective Well–Being Using Smartphone–Based Experience Sampling and GPS Tracking
inferred← citeshttps://doi.org/10.1007/978-3-030-70569-5_2openalex-snapshot
Patient-Independent Schizophrenia Relapse Prediction Using Mobile Sensor Based Daily Behavioral Rhythm Changes
inferred← citeshttps://doi.org/10.1007/978-3-030-98546-2_14openalex-snapshot
Studying Psychopathology in Relation to Smartphone Use: From Self-reports to Objectively Measured Smartphone Use Behavior
inferred← citeshttps://doi.org/10.1007/978-3-031-59717-6_2openalex-snapshot
Individual Behavioral Insights in Schizophrenia: A Network Analysis and Mobile Sensing Approach
inferred← citeshttps://doi.org/10.1007/978-3-031-65126-7_24openalex-snapshot
Fast Convergence Federated Learning with Adaptive Gradient: An Application to Mental Healthcare Monitoring System
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Smartphone-Based Tracking of Sleep in Depression, Anxiety, and Psychotic Disorders
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Digital Phenotyping in Adults with Schizophrenia: A Narrative Review
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Using Graph Representation Learning to Predict Salivary Cortisol Levels in Pancreatic Cancer Patients
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Understanding practices and needs of researchers in human state modeling by passive mobile sensing
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Behind the Screen: A Narrative Review on the Translational Capacity of Passive Sensing for Mental Health Assessment
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Psychological targeting in the age of Big Data
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Differential predictive performance of machine learning models for schizophrenia relapse prediction using behavioral versus physiological passive sensors: A systematic review and meta-analysis
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Towards identifying context-enriched multimodal behavioral patterns for digital phenotyping of human behaviors
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Using digital phenotyping to understand health-related outcomes: A scoping review
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Digital Phenotyping of Mental Health using multimodal sensing of multiple situations of interest: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1016/j.jpsychires.2019.06.002openalex-snapshot
Capturing behavioral indicators of persecutory ideation using mobile technology
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Relationships between smartphone social behavior and relapse in schizophrenia: A preliminary report
inferred← citeshttps://doi.org/10.1016/j.schres.2019.04.003openalex-snapshot
Feasibility of using a smartphone app to assess early signs, basic symptoms and psychotic symptoms over six months: A preliminary report
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The relationship between appraisals of auditory verbal hallucinations and real-time affect and social functioning
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Monitoring Laws: Profiling and Identity in the World State
inferred← citeshttps://doi.org/10.1017/9781108637657.008openalex-snapshot
From Photographic Image to Computer Vision
inferred← citeshttps://doi.org/10.1017/s0033291725000881openalex-snapshot
Predicting experiences of paranoia and auditory verbal hallucinations in daily life with ambulatory sensor data – A feasibility study
inferred← citeshttps://doi.org/10.1038/s41537-020-00123-2openalex-snapshot
Assessing the relationship between routine and schizophrenia symptoms with passively sensed measures of behavioral stability
inferred← citeshttps://doi.org/10.1038/s41537-022-00241-zopenalex-snapshot
Validation of accelerometry as a digital phenotyping measure of negative symptoms in schizophrenia
inferred← citeshttps://doi.org/10.1038/s41598-020-71689-1openalex-snapshot
Using behavioral rhythms and multi-task learning to predict fine-grained symptoms of schizophrenia
inferred← citeshttps://doi.org/10.1038/s41598-021-89768-2openalex-snapshot
Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma
inferred← citeshttps://doi.org/10.1038/s41598-024-69739-zopenalex-snapshot
Mobile sensing-based depression severity assessment in participants with heterogeneous mental health conditions
inferred← citeshttps://doi.org/10.1038/s44222-025-00330-5openalex-snapshot
Mobile medical systems for equitable healthcare
inferred← citeshttps://doi.org/10.1080/10447318.2026.2647542openalex-snapshot
Mobile Sensing Applications for Mental Health: A Scoping Review
inferred← citeshttps://doi.org/10.1093/jssam/smac023openalex-snapshot
Augmenting Survey Data with Digital Trace Data: Is There a Threat to Panel Retention?
inferred← citeshttps://doi.org/10.1093/schbul/sbaa121openalex-snapshot
Geolocation as a Digital Phenotyping Measure of Negative Symptoms and Functional Outcome
inferred← citeshttps://doi.org/10.1093/schbul/sbab134openalex-snapshot
Machine Learning Identifies Digital Phenotyping Measures Most Relevant to Negative Symptoms in Psychotic Disorders: Implications for Clinical Trials
inferred← citeshttps://doi.org/10.1093/schbul/sbaf042openalex-snapshot
Ecological Momentary Assessment of Emotion Regulation and Suicidal Ideation in First-Episode Psychosis
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INTOSIS: Interactive Observation of Smartphone Inferred Symptoms for In-The-Wild Data
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Detection and Analysis of Interrupted Behaviors by Public Policy Interventions during COVID-19
inferred← citeshttps://doi.org/10.1109/jiot.2022.3161046openalex-snapshot
From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques
inferred← citeshttps://doi.org/10.1109/percom45495.2020.9127365openalex-snapshot
On Predicting Relapse in Schizophrenia using Mobile Sensing in a Randomized Control Trial
inferred← citeshttps://doi.org/10.1109/percomw.2019.8730809openalex-snapshot
Robust Health Score Prediction from Pyro-Sensor Activity Data based on Greedy Feature Selection
inferred← citeshttps://doi.org/10.1109/rbme.2018.2851500openalex-snapshot
Technology-Enabled Assessment of Functional Health
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Emotion Recognition in the Real World: Passively Collecting and Estimating Emotions From Natural Speech Data of Individuals With Bipolar Disorder
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Comparative Analysis of Physiological and Speech Signals for State Anxiety Detection in University Students in STEM
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Reasons for Thinking About Suicide Among Individuals With First‐Episode Psychosis: An Ecological Momentary Assessment Study
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Evaluating the utility of digital phenotyping to predict health outcomes in schizophrenia: protocol for the HOPE-S observational study
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Predicting Symptom Trajectories of Schizophrenia Using Mobile Sensing
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The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism
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8th International Workshop on Mental Health and Well-being: Sensing and Intervention
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inferred← citeshttps://doi.org/10.1145/3675094.3678423openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3714394.3750563openalex-snapshot
10$th$ International Workshop on Mental Health and Well-being: From Research to Practice in Mental Healthcare
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inferred← citeshttps://doi.org/10.1186/s12888-026-08157-zopenalex-snapshot
Digital phenotyping for predicting relapse in psychiatric disorders: a systematic review of passive sensing approaches
inferred← citeshttps://doi.org/10.1371/journal.pdig.0000734openalex-snapshot
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inferred← citeshttps://doi.org/10.1371/journal.pone.0266516openalex-snapshot
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inferred← citeshttps://doi.org/10.18653/v1/2023.emnlp-main.734openalex-snapshot
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inferred← citeshttps://doi.org/10.2196/17662openalex-snapshot
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inferred← citeshttps://doi.org/10.2196/19962openalex-snapshot
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inferred← citeshttps://doi.org/10.2196/31006openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fpsyt.2021.642200openalex-snapshot
mHealth-Assisted Detection of Precursors to Relapse in Schizophrenia
inferred← citeshttps://doi.org/10.3390/s22103893openalex-snapshot
Opportunities for Smartphone Sensing in E-Health Research: A Narrative Review
inferred← citeshttps://doi.org/10.3390/s24020348openalex-snapshot
Machine Learning for Multimodal Mental Health Detection: A Systematic Review of Passive Sensing Approaches
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Pluralismes explicatif et axiologique de la psychiatrie contemporaine et conception de classifications : le cas des Research Domain Criteria
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Science and Advanced Computing — runs a structured editorial panel for researchers
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