Psychiatry

Effectiveness of robot therapy in the management of behavioural and psychological symptoms for individuals with dementia: A systematic review and meta-analysis.

Robot therapy presents a promising alternative in dementia care. However, its effectiveness has not been verified comprehensively. This systematic review and meta-analysis aim at evaluating the effectiveness of robot therapy in the management of behavioural and psychological symptoms for individuals with dementia. Studies assessing the effectiveness of robot therapy were identified using 10 academ...

Schizophrenia: A Survey of Artificial Intelligence Techniques Applied to Detection and Classification.

Artificial Intelligence in healthcare employs machine learning algorithms to emulate human cognition in the analysis of complicated or large sets of data. Specifically, artificial intelligence taps on the ability of computer algorithms and software with allowable thresholds to make deterministic approximate conclusions. In comparison to traditional technologies in healthcare, artificial intelligen...

Intelligent Recognition of Hospital Image Based on Deep Learning: The Relationship between Adaptive Behavior and Family Function in Children with ADHD.

Chronic diseases are gradually becoming the main threat to human health. By designing an efficient hospital management platform to quickly identify th...

Classification of Mental Stress Using CNN-LSTM Algorithms with Electrocardiogram Signals.

The mental stress faced by many people in modern society is a factor that causes various chronic diseases, such as depression, cancer, and cardiovascu...

Pivotal Response Treatment with and without robot-assistance for children with autism: a randomized controlled trial.

Pivotal response treatment (PRT) is a promising intervention focused on improving social communication skills in children with autism spectrum disorde...

Depression Diagnosis Modeling With Advanced Computational Methods: Frequency-Domain eMVAR and Deep Learning.

Electroencephalogram (EEG)-based automated depression diagnosis systems have been suggested for early and accurate detection of mood disorders. EEG si...

Robust diagnostic classification via Q-learning.

Machine learning (ML) models have demonstrated the power of utilizing clinical instruments to provide tools for domain experts in gaining additional i...

Predicting anxiety in cancer survivors presenting to primary care - A machine learning approach accounting for physical comorbidity.

BACKGROUND: The purpose of this study was to explore predictors for anxiety as the most common form of psychological distress in cancer survivors whil...

Twelve patients with mental illness who complained of postprandial symptoms in addition to fatigue showed central adrenal insufficiency.

BACKGROUND: Adrenal insufficiency (AI) may cause psychiatric symptoms. We evaluated the correlation between the hypothalamic-pituitary-adrenal axis (H...

Robot-mediated interventions for teaching children with ASD: A new intraverbal skill.

Socially assistive robots (SAR) have the potential to impact therapies for Autism Spectrum Disorder (ASD) by supporting clinicians in increasing learn...

Effects of spectral features of EEG signals recorded with different channels and recording statuses on ADHD classification with deep learning.

Early diagnosis of attention deficit and hyperactivity disorder (ADHD) by experts is difficult. Some solutions using electroencephalography (EEG) sign...

Robot-Assisted Autism Therapy (RAAT). Criteria and Types of Experiments Using Anthropomorphic and Zoomorphic Robots. Review of the Research.

Supporting the development of a child with autism is a multi-profile therapeutic work on disturbed areas, especially understanding and linguistic expr...

Evaluating atypical language in autism using automated language measures.

Measurement of language atypicalities in Autism Spectrum Disorder (ASD) is cumbersome and costly. Better language outcome measures are needed. Using l...

For whom should psychotherapy focus on problem coping? A machine learning algorithm for treatment personalization.

OBJECTIVE: We aimed to develop and test an algorithm for individual patient predictions of problem coping experiences (PCE) (i.e., patients' understan...

Improvements to PTSD quality metrics with natural language processing.

RATIONALE AIMS AND OBJECTIVES: As quality measurement becomes increasingly reliant on the availability of structured electronic medical record (EMR) d...

Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm.

Clinical visit data are clustered within people, which complicates prediction modeling. Cluster size is often informative because people receiving mor...

Cross-evaluation of social mining for classification of depressed online personas.

With the continuous increase in the use of social networks, social mining is steadily becoming a powerful component of digital phenotyping. In this pa...

Identification of voxel-based texture abnormalities as new biomarkers for schizophrenia and major depressive patients using layer-wise relevance propagation on deep learning decisions.

Non-segmented MRI brain images are used for the identification of new Magnetic Resonance Imaging (MRI) biomarkers able to differentiate between schizo...

Effects of gait training with a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), on quality of life in patients with neuromuscular disease, able to walk independently with aids.

Robot-assisted gait training using a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), has been shown to improve the mobility of patients...

EEG microstate features for schizophrenia classification.

Electroencephalography (EEG) microstate analysis is a method wherein spontaneous EEG activity is segmented at sub-second levels to analyze quasi-stabl...