Psychiatry

Stress Classification Using Brain Signals Based on LSTM Network.

The early diagnosis of stress symptoms is essential for preventing various mental disorder such as d...

Predictive models for clinical decision making: Deep dives in practical machine learning.

The deployment of machine learning for tasks relevant to complementing standard of care and advancin...

Depression screening using a non-verbal self-association task: A machine-learning based pilot study.

BACKGROUND: Effective screening is important to combat the raising burden of depression and opens a ...

Exploring the Employment Quality Evaluation Model of Application-Oriented University Graduates by Deep Learning.

In view of the employment difficulties of college graduates, this paper analyzes the overflow of gra...

Building trust in artificial intelligence and new technologies in mental health.

Effectiveness and safety of blonanserin for improving social and cognitive functions in patients with first-episode schizophrenia: a study protocol for a prospective, multicentre, single-arm clinical trial.

INTRODUCTION: Both the pharmacological characteristics of blonanserin and its related small sample s...

Assessing Schizophrenia Patients Through Linguistic and Acoustic Features Using Deep Learning Techniques.

Thought, language, and communication disorders are among the salient characteristics of schizophreni...

Employing biochemical biomarkers for building decision tree models to predict bipolar disorder from major depressive disorder.

BACKGROUND: Conventional biochemical parameters may have predictive values for use in clinical ident...

Psychosocial Factors and Psychological Characteristics of Personality of Patients with Chronic Diseases Using Artificial Intelligence Data Mining Technology and Wireless Network Cloud Service Platform.

It was to explore the application value of health cloud service platform based on data mining algori...

Identifying Visual Attention Features Accurately Discerning Between Autism and Typically Developing: a Deep Learning Framework.

Atypical visual attention is a hallmark of autism spectrum disorder (ASD). Identifying the attention...

Large-Scale Textual Datasets and Deep Learning for the Prediction of Depressed Symptoms.

Millions of people worldwide suffer from depression. Assessing, treating, and preventing recurrence ...

Endoscopic Enucleation of the Prostate Is Better than Robot-assisted Simple Prostatectomy.

In 2022, endoscopic enucleation of the prostate (EEP) is the treatment of choice for benign prostati...

Deep Learning Enabled Diagnosis of Children's ADHD Based on the Big Data of Video Screen Long-Range EEG.

Attention-deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children....

Facial Features Detection System To Identify Children With Autism Spectrum Disorder: Deep Learning Models.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with brain development th...

Conversational Artificial Intelligence in Psychotherapy: A New Therapeutic Tool or Agent?

Conversational artificial intelligence (CAI) presents many opportunities in the psychotherapeutic la...

Multimodal treatment efficacy differs in dependence of core symptom profiles in adult Attention-Deficit/Hyperactivity Disorder: An analysis of the randomized controlled COMPAS trial.

There is broad consensus that to improve the treatment of adult Attention-Deficit/Hyperactivity Diso...

Association of Selective Serotonin Reuptake Inhibitor Use With Abnormal Physical Movement Patterns as Detected Using a Piezoelectric Accelerometer and Deep Learning in a Nationally Representative Sample of Noninstitutionalized Persons in the US.

IMPORTANCE: Selective serotonin reuptake inhibitors (SSRIs) are a common first-line treatment for so...

Automated Facial Expression Recognition Framework Using Deep Learning.

Facial expression is one of the most significant elements which can tell us about the mental state o...

InsuLock: A Weakly Supervised Learning Approach for Accurate Insulator Prediction, and Variant Impact Quantification.

Mapping chromatin insulator loops is crucial to investigating genome evolution, elucidating critical...

Quantifying depression-related language on social media during the COVID-19 pandemic.

INTRODUCTION: The COVID-19 pandemic had clear impacts on mental health. Social media presents an opp...

Detection of Types of Mental Illness through the Social Network Using Ensembled Deep Learning Model.

In today's era, social networking platforms are widely used to share emotions. These types of emotio...