Psychiatry

Deep Learning-based detection of psychiatric attributes from German mental health records.

BACKGROUND: Health care records provide large amounts of data with real-world and longitudinal aspec...

Identifying and Predicting Autism Spectrum Disorder Based on Multi-Site Structural MRI With Machine Learning.

Although emerging evidence has implicated structural/functional abnormalities of patients with Autis...

Mood State Detection in Handwritten Tasks Using PCA-mFCBF and Automated Machine Learning.

In this research, we analyse data obtained from sensors when a user handwrites or draws on a tablet ...

Comparing Deep Learning and Conventional Machine Learning Models for Predicting Mental Illness from History of Present Illness Notations.

Mental illness, a serious problem across the globe, requires multi-pronged solutions including effec...

Mental speed is high until age 60 as revealed by analysis of over a million participants.

Response speeds in simple decision-making tasks begin to decline from early and middle adulthood. Ho...

Machine learning classification of schizophrenia patients and healthy controls using diverse neuroanatomical markers and Ensemble methods.

Schizophrenia is a major psychiatric disorder that imposes enormous clinical burden on patients and ...

Flexible Neural Network Realized by the Probabilistic SiO Memristive Synaptic Array for Energy-Efficient Image Learning.

The human brain's neural networks are sparsely connected via tunable and probabilistic synapses, whi...

Can natural language processing models extract and classify instances of interpersonal violence in mental healthcare electronic records: an applied evaluative study.

OBJECTIVE: This paper evaluates the application of a natural language processing (NLP) model for ext...

Deep learning model using retinal vascular images for classifying schizophrenia.

Contemporary psychiatric diagnosis still relies on the subjective symptom report of the patient duri...

Medically-oriented design for explainable AI for stress prediction from physiological measurements.

BACKGROUND: In the last decade, a lot of attention has been given to develop artificial intelligence...

Automated detection of clinical depression based on convolution neural network model.

As a common mental disorder, depression is placing an increasing burden on families and society. How...

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

Although most statistical methods for the analysis of longitudinal data have focused on retrospectiv...

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, ...

Early colorectal lesion (depressed type) detected using artificial intelligence.

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....

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 ...

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 da...

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...

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 ...

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, whi...

Effects of Parental Involvement in Robot-Assisted Autism Therapy.

Parental involvement in traditional autism therapy is key to the effective treatment of children wit...