Prerna Chikersal
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View article: Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation
Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation Open
Background Longitudinal tracking of multiple sclerosis (MS) symptoms in an individual’s environment may improve self-monitoring and clinical management for people with MS. Conventional symptom tracking methods rely on self-reports and clin…
View article: Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation (Preprint)
Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation (Preprint) Open
BACKGROUND Longitudinal tracking of multiple sclerosis (MS) symptoms in an individual’s environment may improve self-monitoring and clinical management for people with MS. Conventional symptom tracking methods rely on self-reports and cli…
View article: Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments
Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments Open
Background Longitudinal tracking of multiple sclerosis (MS) symptoms in an individual’s own environment may improve self-monitoring and clinical management for people with MS (pwMS). Objective We present a machine learning approach that en…
View article: Correction: Speaking out of turn: How video conferencing reduces vocal synchrony and collective intelligence
Correction: Speaking out of turn: How video conferencing reduces vocal synchrony and collective intelligence Open
[This corrects the article DOI: 10.1371/journal.pone.0247655.].
View article: Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping
Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping Open
Background The COVID-19 pandemic has broad negative impact on the physical and mental health of people with chronic neurological disorders such as multiple sclerosis (MS). Objective We presented a machine learning approach leveraging passi…
View article: Objective Measurement of Hyperactivity Using Mobile Sensing and Machine Learning: Pilot Study
Objective Measurement of Hyperactivity Using Mobile Sensing and Machine Learning: Pilot Study Open
Background Although hyperactivity is a core symptom of attention-deficit/hyperactivity disorder (ADHD), there are no objective measures that are widely used in clinical settings. Objective We describe the development of a smartwatch app to…
View article: Objective Measurement of Hyperactivity Using Mobile Sensing and Machine Learning: Pilot Study (Preprint)
Objective Measurement of Hyperactivity Using Mobile Sensing and Machine Learning: Pilot Study (Preprint) Open
BACKGROUND Although hyperactivity is a core symptom of attention-deficit/hyperactivity disorder (ADHD), there are no objective measures that are widely used in clinical settings. OBJECTIVE We describe the development of a smartwatch app…
View article: Leveraging Collaborative-Filtering for Personalized Behavior Modeling
Leveraging Collaborative-Filtering for Personalized Behavior Modeling Open
The prevalence of mobile phones and wearable devices enables the passive capturing and modeling of human behavior at an unprecedented resolution and scale. Past research has demonstrated the capability of mobile sensing to model aspects of…
View article: Speaking out of turn: How video conferencing reduces vocal synchrony and collective intelligence
Speaking out of turn: How video conferencing reduces vocal synchrony and collective intelligence Open
Collective intelligence (CI) is the ability of a group to solve a wide range of problems. Synchrony in nonverbal cues is critically important to the development of CI; however, extant findings are mostly based on studies conducted face-to-…
View article: Prosodic Synchrony Experiment set up PLoS One 2021 v1
Prosodic Synchrony Experiment set up PLoS One 2021 v1 Open
Collective intelligence (CI) is the ability of a group to solve a wide range of problems.Synchrony in nonverbal cues is critically important to the development of CI; however, extant findings are mostly based on studies conducted face-to-f…
View article: Understanding Client Support Strategies to Improve Clinical Outcomes in an Online Mental Health Intervention
Understanding Client Support Strategies to Improve Clinical Outcomes in an Online Mental Health Intervention Open
Online mental health interventions are increasingly important in providing access to, and supporting the effectiveness of, mental health treatment. While these technologies are effective, user attrition and early disengagement are key chal…
View article: 0258 Early Semester Sleep Variability Predicts Depression Among College Students
0258 Early Semester Sleep Variability Predicts Depression Among College Students Open
Introduction Sleep is a critical behavior predicting mental health and depressive symptomatology in young adults.The extant scientific literature generally focuses on self-reported sleep measures over relatively short time frames. Here, we…
View article: Leveraging Routine Behavior and Contextually-Filtered Features for Depression Detection among College Students
Leveraging Routine Behavior and Contextually-Filtered Features for Depression Detection among College Students Open
The rate of depression in college students is rising, which is known to increase suicide risk, lower academic performance and double the likelihood of dropping out of school. Existing work on finding relationships between passively sensed …
View article: Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning of Smartphone and Fitbit Data
Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning of Smartphone and Fitbit Data Open
Passive sensing has the potential for detecting loneliness in college students and identifying the associated behavioral patterns. These findings highlight intervention opportunities through mobile technology to reduce the impact of loneli…
View article: Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning of Smartphone and Fitbit Data (Preprint)
Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning of Smartphone and Fitbit Data (Preprint) Open
BACKGROUND Feelings of loneliness are associated with poor physical and mental health. Detection of loneliness through passive sensing on personal devices can lead to the development of interventions aimed at decreasing rates of lonelines…
View article: SeNTU: Sentiment Analysis of Tweets by Combining a Rule-based Classifier with Supervised Learning
SeNTU: Sentiment Analysis of Tweets by Combining a Rule-based Classifier with Supervised Learning Open
We describe a Twitter sentiment analysis system developed by combining a rule-based classifier with supervised learning.We submitted our results for the message-level subtask in SemEval 2015 Task 10, and achieved a F 1 -score of 57.06%.The…