Psychiatry

Investigating the increase in the specialized performance of athletes using artificial neural network (ANN) exercises.

Badminton, a dynamic and fast-paced racket sport, demands a unique combination of physical, technical, and cognitive abilities from its players. This study investigates the impact of a tailored core strength training program on the specialized performance of elite badminton athletes, with the aim of unlocking their full potential and improving overall well-being. The research involved a cohort of ...

Neuronal and therapeutic perspectives on empathic pain: A rational insight.

Empathy is the capacity to experience and understand the feelings of others, thereby playing a key role in a person's mental well-being essentially by promoting kindness and a sense of belongingness to the group. However, too much empathy may result in psychological problems such as empathic distress, compassion fatigue, and burnout, collectively termed empathic pain. Several brain regions are imp...

Altered resting-state brain activity in patients with major depression disorder and bipolar disorder: A regional homogeneity analysis.

BACKGROUND: Major Depressive Disorder (MDD) and Bipolar Disorder (BD) exhibit overlapping depressive symptoms, complicating their differentiation in c...

Using machine learning methods to predict the outcome of psychological therapies for post-traumatic stress disorder: A systematic review.

BACKGROUND: A number of treatments are available for post-traumatic stress disorder (PTSD), however, there is currently a lack of data-driven treatmen...

Individual and integrated indexes of inflammation predicting the risks of mental disorders - statistical analysis and artificial neural network.

OBJECTIVE: The prevalence of mental illness in Taiwan increased. Identifying and mitigating risk factors for mental illness is essential. Inflammation...

Develop and validate machine learning models to predict the risk of depressive symptoms in older adults with cognitive impairment.

BACKGROUND: Cognitive impairment and depressive symptoms are prevalent and closely interrelated mental health issues in the elderly. Traditional metho...

Feasibility of Using ChatGPT to Generate Exposure Hierarchies for Treating Obsessive-Compulsive Disorder.

Obsessive-compulsive disorder (OCD) is a chronic, severe condition. Although exposure and response prevention (ERP), the first-line treatment for OCD,...

Generative AI-Enabled Therapy Support Tool for Improved Clinical Outcomes and Patient Engagement in Group Therapy: Real-World Observational Study.

BACKGROUND: Cognitive behavioral therapy (CBT) is a highly effective treatment for depression and anxiety disorders. Nonetheless, a substantial propor...

Female autism categorization using CNN based NeuroNet57 and ant colony optimization.

Autism identification and classification using biomedical medical image analysis has advanced recently. Research shows autistic females have different...

MCDGLN: Masked connection-based dynamic graph learning network for autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by complex physiological processes. Previous research has predominantly ...

Continuous nursing symptom management in cancer chemotherapy patients using deep learning.

To assess the efficacy of a deep learning platform for managing symptoms in chemotherapy patients, aiming to enhance their quality of life. A non-rand...

Prediction of postpartum depression in women: development and validation of multiple machine learning models.

BACKGROUND: Postpartum depression (PPD) is a significant public health issue. This study aimed to develop and validate machine learning (ML) models us...

The More, the Better? Evaluating the Role of EEG Preprocessing for Deep Learning Applications.

The last decade has witnessed a notable surge in deep learning applications for electroencephalography (EEG) data analysis, showing promising improvem...

Comparison of an AI Chatbot With a Nurse Hotline in Reducing Anxiety and Depression Levels in the General Population: Pilot Randomized Controlled Trial.

BACKGROUND: Artificial intelligence (AI) chatbots have been customized to deliver on-demand support for people with mental health problems. However, t...

AI anxiety and knowledge payment: the roles of perceived value and self-efficacy.

BACKGROUND: The integration of Artificial Intelligence (AI) into daily life raises significant challenges and uncertainties, notably concerning job se...

Applying AI in the Context of the Association Between Device-Based Assessment of Physical Activity and Mental Health: Systematic Review.

BACKGROUND: Wearable technology is used by consumers worldwide for continuous activity monitoring in daily life but more recently also for classifying...

Using Natural Language Processing Methods to Build the Hypersexuality in Bipolar Reddit Corpus: Infodemiology Study of Reddit.

BACKGROUND: Bipolar is a severe mental health condition affecting at least 2% of the global population, with clinical observations suggesting that ind...

AdaptEEG: A Deep Subdomain Adaptation Network With Class Confusion Loss for Cross-Subject Mental Workload Classification.

EEG signals exhibit non-stationary characteristics, particularly across different subjects, which presents significant challenges in the precise class...

On-Chip Mental Stress Detection: Integrating a Wearable Behind-The-Ear EEG Device With Embedded Tiny Neural Network.

The study introduces an innovative approach to efficient mental stress detection by combining electroencephalography (EEG) analysis with on-chip neura...

Research on prediction model of adolescent suicide and self-injury behavior based on machine learning algorithm.

OBJECTIVE: To explore the risk factors that affect adolescents' suicidal and self-injurious behaviors and to construct a prediction model for adolesce...