Psychiatry

Neural networks for clustered and longitudinal data using mixed effects models.

Although most statistical methods for the analysis of longitudinal data have focused on retrospective models of association, new advances in mobile health data have presented opportunities for predicting future health status by leveraging an individual's behavioral history alongside data from similar patients. Methods that incorporate both individual-level and sample-level effects are critical to ...

AI-Based Publicity Strategies for Medical Colleges: A Case Study of Healthcare Analysis.

The health status and cognition of undergraduates, especially the scientific concept of healthcare, are particularly important for the overall development of society and themselves. The survey shows that there is a significant lack of knowledge about healthcare among undergraduates in medical college, even among medical undergraduates, not to mention non-medical undergraduates. Therefore, it is a ...

Performance Evaluation of EEG Based Mental Stress Assessment Approaches for Wearable Devices.

Mental stress has been identified as the root cause of various physical and psychological disorders. Therefore, it is crucial to conduct timely diagno...

An Interpretable Machine Learning Approach to Predict Fall Risk Among Community-Dwelling Older Adults: a Three-Year Longitudinal Study.

BACKGROUND: Adverse health effects resulting from falls are a major public health concern. Although studies have identified risk factors for falls, no...

Evaluation of Machine Learning Techniques to Predict the Likelihood of Mental Health Conditions Following a First mTBI.

OBJECTIVE: Limited research has evaluated the utility of machine learning models and longitudinal data from electronic health records (EHR) to forecas...

Detecting Presence of PTSD Using Sentiment Analysis From Text Data.

Rates of Post-traumatic stress disorder (PTSD) have risen significantly due to the COVID-19 pandemic. Telehealth has emerged as a means to monitor sym...

Continuous Scoring of Depression From EEG Signals via a Hybrid of Convolutional Neural Networks.

Depression score is traditionally determined by taking the Beck depression inventory (BDI) test, which is a qualitative questionnaire. Quantitative sc...

Novel Decision-Making Techniques in Tripolar Fuzzy Environment with Application: A Case Study of ERP Systems.

The intuitionistic fuzzy set (IFS) and bipolar fuzzy set (BFS) are all effective models to describe ambiguous and incomplete cognitive knowledge with ...

Effects of Parental Involvement in Robot-Assisted Autism Therapy.

Parental involvement in traditional autism therapy is key to the effective treatment of children with ASD. Little is known about parental involvement ...

A Preliminary Study on Realizing Human-Robot Mental Comforting Dialogue via Sharing Experience Emotionally.

Mental health issues are receiving more and more attention in society. In this paper, we introduce a preliminary study on human-robot mental comfortin...

Deep learning-based school attendance prediction for autistic students.

Autism Spectrum Disorder is a neurodevelopmental disorder characterized by deficits in social communication and interaction as well as the presence of...

A Systematic Review of Research on Robot-Assisted Therapy for Children with Autism.

Recent studies have shown that children with autism may be interested in playing with an interactive robot. Moreover, the robot can engage these child...

Analysis of Clinical Parameters, Drug Consumption and Use of Health Resources in a Southern European Population with Alcohol Abuse Disorder during COVID-19 Pandemic.

The disruption in healthcare attention to people with alcohol dependence, along with psychological decompensation as a consequence of lockdown derived...

DOTA: Deep Learning Optimal Transport Approach to Advance Drug Repositioning for Alzheimer's Disease.

Alzheimer's disease (AD) is the leading cause of age-related dementia, affecting over 5 million people in the United States and incurring a substantia...

Evaluation of deep convolutional neural networks for in situ hybridization gene expression image representation.

High resolution in situ hybridization (ISH) images of the brain capture spatial gene expression at cellular resolution. These spatial profiles are key...

Annual Research Review: Translational machine learning for child and adolescent psychiatry.

Children and adolescents could benefit from the use of predictive tools that facilitate personalized diagnoses, prognoses, and treatment selection. Su...

Behavioral Data Analysis of Robot-Assisted Autism Spectrum Disorder (ASD) Interventions Based on Lattice Computing Techniques.

Recent years have witnessed the proliferation of social robots in various domains including special education. However, specialized tools to assess th...

Application of deep learning algorithm on whole genome sequencing data uncovers structural variants associated with multiple mental disorders in African American patients.

Mental disorders present a global health concern, while the diagnosis of mental disorders can be challenging. The diagnosis is even harder for patient...

Classifying social determinants of health from unstructured electronic health records using deep learning-based natural language processing.

OBJECTIVE: Social determinants of health (SDOH) are non-medical factors that can profoundly impact patient health outcomes. However, SDOH are rarely a...

Intelligent Fault Diagnosis Framework for Modular Multilevel Converters in HVDC Transmission.

Open circuit failure mode in insulated-gate bipolar transistors (IGBT) is one of the most common faults in modular multilevel converters (MMCs). Sever...