Psychiatry

Image Features of Resting-State Functional Magnetic Resonance Imaging in Evaluating Poor Emotion and Sleep Quality in Patients with Chronic Pain under Artificial Intelligence Algorithm.

The balanced iterative reducing and clustering using hierarchies (BIRCH) method was adopted to optimize the results of the resting-state functional magnetic resonance imaging (RS-fMRI) to analyze the changes in the brain function of patients with chronic pain accompanied by poor emotion or abnormal sleep quality in this study, so as to provide data support for the prevention and treatment of clini...

Artificially intelligent chatbots in digital mental health interventions: a review.

INTRODUCTION: Increasing demand for mental health services and the expanding capabilities of artificial intelligence (AI) in recent years has driven the development of digital mental health interventions (DMHIs). To date, AI-based chatbots have been integrated into DMHIs to support diagnostics and screening, symptom management and behavior change, and content delivery.

Robotically-induced hallucination triggers subtle changes in brain network transitions.

The perception that someone is nearby, although nobody can be seen or heard, is called presence hallucination (PH). Being a frequent hallucination in ...

Evaluation of the correlation between gaze avoidance and schizophrenia psychopathology with deep learning-based emotional recognition.

OBJECTIVE: To investigate the correlation between gaze avoidance and psychopathology in patients with schizophrenia through eye movement measurements ...

Income inequalities, social support and depressive symptoms among older adults in Europe: a multilevel cross-sectional study.

UNLABELLED: This study analysed the association between income inequality and depression from a multilevel perspective among older adults in Europe, i...

Associations between depressive symptoms and disease progression in older patients with chronic kidney disease: results of the EQUAL study.

BACKGROUND: Depressive symptoms are associated with adverse clinical outcomes in patients with end-stage kidney disease; however, few small studies ha...

A New Socially Assistive Robot with Integrated Serious Games for Therapies with Children with Autism Spectrum Disorder and Down Syndrome: A Pilot Study.

This work introduces a new socially assistive robot termed MARIA T21 (meaning "Mobile Autonomous Robot for Interaction with Autistics", with the addit...

Detection of child depression using machine learning methods.

BACKGROUND: Mental health problems, such as depression in children have far-reaching negative effects on child, family and society as whole. It is nec...

Determination of quetiapine and its metabolites in plasma by field-enhanced sample stacking.

Quetiapine is an atypical antipsychotic drug that can be used to treat mental disorders, including schizophrenia, bipolar disorder and Alzheimer's dis...

Natural Language Processing markers in first episode psychosis and people at clinical high-risk.

Recent work has suggested that disorganised speech might be a powerful predictor of later psychotic illness in clinical high risk subjects. To that en...

Digital biomarkers of anxiety disorder symptom changes: Personalized deep learning models using smartphone sensors accurately predict anxiety symptoms from ecological momentary assessments.

Smartphones are capable of passively capturing persons' social interactions, movement patterns, physiological activation, and physical environment. Ne...

Enhancing electrocardiographic analysis by combining a high-resolution 12-lead ECG with novel software tools.

INTRODUCTION: Signal-averaged electrocardiography is a non-invasive, computerized technique that amplifies, filters, and averages cardiac electrical s...

AI ethics in computational psychiatry: From the neuroscience of consciousness to the ethics of consciousness.

Methods used in artificial intelligence (AI) overlap with methods used in computational psychiatry (CP). Hence, considerations from AI ethics are also...

Machine Learning-Based HIV Risk Estimation Using Incidence Rate Ratios.

HIV/AIDS is an ongoing global pandemic, with an estimated 39 million infected worldwide. Early detection is anticipated to help improve outcomes and p...

Understanding Medical Distrust Among African American/Black and Latino Persons Living With HIV With Sub-Optimal Engagement Along the HIV Care Continuum: A Machine Learning Approach.

Medical distrust is a potent barrier to participation in HIV care and medication use among African American/Black and Latino (AABL) persons living wit...

A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD.

The pathological mechanism of attention deficit hyperactivity disorder (ADHD) is incompletely specified, which leads to difficulty in precise diagnosi...

A Shrewd Artificial Neural Network-Based Hybrid Model for Pervasive Stress Detection of Students Using Galvanic Skin Response and Electrocardiogram Signals.

Mental illness issues are a very common health issue in youths and adults across the world. The usage of real-time data analytics in health care has a...

Prediction of PCOS and Mental Health Using Fuzzy Inference and SVM.

Polycystic ovarian syndrome (PCOS) is a hormonal disorder found in women of reproductive age. There are different methods used for the detection of PC...

Mental Stress Classification Based on a Support Vector Machine and Naive Bayes Using Electrocardiogram Signals.

Examining mental health is crucial for preventing mental illnesses such as depression. This study presents a method for classifying electrocardiogram ...

Embracing the disharmony in medical imaging: A Simple and effective framework for domain adaptation.

Domain shift, the mismatch between training and testing data characteristics, causes significant degradation in the predictive performance in multi-so...