Psychiatry

A deep learning approach in automated detection of schizophrenia using scalogram images of EEG signals.

This study presents a method with high accuracy performance that aims to automatically detect schizophrenia (SZ) from electroencephalography (EEG) records. Unlike related literature studies using traditional machine learning algorithms, the features required for the training of the network are automatically extracted from the EEG records in our method. In order to obtain the time frequency feature...

Editorial comment on "Diagnosing autism spectrum disorder in children using conventional MRI and apparent diffusion coefficient based deep learning algorithms".

This editorial comment refers to the article: "Diagnosing autism spectrum disorder in children using conventional MRI and apparent diffusion coefficient based deep learning algorithms" by Guo et al. (Eur Radiol, 2021). KEY POINTS: •Deep learning may help to uncover imaging features of autism spectrum disorder on MRI.

Network analysis of trauma in patients with early-stage psychosis.

Childhood trauma (ChT) is a risk factor for psychosis. Negative lifestyle factors such as rumination, negative schemas, and poor diet and exercise are...

Intelligent Monitoring of Care Status for COPD Patients Based on Deep Learning.

To discuss the application method and effect of COPD patients in deep learning in intelligent monitoring, two groups were used under a reasonable sele...

Plasma neurofilament light chain protein is not increased in treatment-resistant schizophrenia and first-degree relatives.

OBJECTIVE: Schizophrenia, a complex psychiatric disorder, is often associated with cognitive, neurological and neuroimaging abnormalities. The process...

Training method and system for stress management and mental health care of managers based on deep learning.

In recent years, with the rapid development of the economy, in order to stabilize in the market and expand their own business, various companies in th...

Treatment selection using prototyping in latent-space with application to depression treatment.

Machine-assisted treatment selection commonly follows one of two paradigms: a fully personalized paradigm which ignores any possible clustering of pat...

Mechanisms and Methods to Understand Depressive Symptoms.

Depressive symptoms, feelings of sadness, anger, and loss that interfere with a person's daily life, are prevalent health concerns across populations ...

Diagnosis of Schizophrenia Based on Deep Learning Using fMRI.

Schizophrenia is a brain disease that frequently occurs in young people. Early diagnosis and treatment can reduce family burdens and reduce social cos...

Predicting suicidal thoughts and behavior among adolescents using the risk and protective factor framework: A large-scale machine learning approach.

INTRODUCTION: Addressing the problem of suicidal thoughts and behavior (STB) in adolescents requires understanding the associated risk factors. While ...

Using CatBoost algorithm to identify middle-aged and elderly depression, national health and nutrition examination survey 2011-2018.

Depression is one of the most common mental health problems in middle-aged and elderly people. The establishment of risk factor-based depression risk ...

Deep learning for neuroimaging-based diagnosis and rehabilitation of Autism Spectrum Disorder: A review.

Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective rehabilitation is essential for the management of this disorder. Artificial...

Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study.

The placebo effect across psychiatric disorders is still not well understood. In the present study, we conducted meta-analyses including meta-regressi...

Using deep learning to classify pediatric posttraumatic stress disorder at the individual level.

BACKGROUND: Children exposed to natural disasters are vulnerable to developing posttraumatic stress disorder (PTSD). Previous studies using resting-st...

Enriching Human-Robot Interaction with Mobile App in Interventions of Children with Autism Spectrum Disorder.

: Autism spectrum disorder (ASD) is a group of complex lifelong neurodevelopmental disorders, characterized by difficulties in social communication an...

How prevalent and severe is addiction on GABAmimetic drugs in an elderly German general hospital population? Focus on gabapentinoids, benzodiazepines, and z-hypnotic drugs.

OBJECTIVE: Gabapentinoids (GPT) are reported to be increasingly misused by opioid- and polydrug-users, but the addictive potential of GPT outside of t...

Color painting predicts clinical symptoms in chronic schizophrenia patients via deep learning.

BACKGROUND: Individuals with psychiatric disorders perceive the world differently. Previous studies indicated impaired color vision and weakened color...

Model Construction of Using Physiological Signals to Detect Mental Health Status.

BACKGROUND: Mental health is a direct indicator of human mental activity, and it also affects all aspects of the human body. It plays a very important...

Prediction of Readmission in Geriatric Patients From Clinical Notes: Retrospective Text Mining Study.

BACKGROUND: Prior literature suggests that psychosocial factors adversely impact health and health care utilization outcomes. However, psychosocial fa...

Natural language processing for cognitive therapy: Extracting schemas from thought records.

The cognitive approach to psychotherapy aims to change patients' maladaptive schemas, that is, overly negative views on themselves, the world, or the ...