Psychiatry

Determinants of implementing of pet robots in nursing homes for dementia care.

BACKGROUND: Pet robots have been employed as viable substitutes to pet therapy in nursing homes. Despite their potential to enhance the psychosocial health of residents with dementia, there is a lack of studies that have investigated determinants of implementing pet robots in real-world practice. This study aims to explore the determinants of implementing pet robots for dementia care in nursing ho...

Arabic Speech Analysis for Classification and Prediction of Mental Illness due to Depression Using Deep Learning.

Depression is a global prevalent ailment for possible mental illness or mental disorder globally. Recognizing depressed early signs is critical for evaluating and preventing mental illness. With the progress of machine learning, it is possible to make intelligent systems capable of detecting depressive symptoms using speech analysis. This study presents a hybrid model to identify and predict menta...

Engaging Through Awareness: Purpose-Driven Framework Development to Evaluate and Develop Future Business Strategies With Exponential Technologies Toward Healthcare Democratization.

Industry 4.0 and digital transformation will likely come with an era of changes for most manufacturers and tech industries, and even healthcare delive...

Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records.

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired so...

DNA Memristors and Their Application to Reservoir Computing.

This paper introduces memristors realized by molecular and DNA reactions. Molecular memristors process one input molecule, generate two output molecul...

A deep learning based method for intelligent detection of seafarers' mental health condition.

Mental health monitoring of seafarers is an important part of achieving normal development of the ocean shipping industry. In this paper, a dual subje...

Using Convolutional Neural Networks for the Assessment Research of Mental Health.

Existing mental health assessment methods mainly rely on experts' experience, which has subjective bias, so convolutional neural networks are applied ...

Continuous-time probabilistic models for longitudinal electronic health records.

Analysis of longitudinal Electronic Health Record (EHR) data is an important goal for precision medicine. Difficulty in applying Machine Learning (ML)...

Suicide Risk Prediction in Clinical Settings-Additional Considerations for Face-to-Face Screening and Machine Learning Approaches.

Detection of schizophrenia using hybrid of deep learning and brain effective connectivity image from electroencephalogram signal.

Detection of mental disorders such as schizophrenia (SZ) through investigating brain activities recorded via Electroencephalogram (EEG) signals is a p...

Stress Classification Using Brain Signals Based on LSTM Network.

The early diagnosis of stress symptoms is essential for preventing various mental disorder such as depression. Electroencephalography (EEG) signals ar...

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 advancing tools for precision health has gained much atten...

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 critical time window for early intervention. Clini...

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 graduates in a particular period caused by the expans...

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 size studies suggest that blonanserin could allevia...

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

Thought, language, and communication disorders are among the salient characteristics of schizophrenia. Such impairments are often exhibited in patient...

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 identification between bipolar disorder (BD) and major ...

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 algorithm and wireless network in the analysis of psycho...

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 features accurately discerning between people wit...

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 requires early detection of depressive symptoms as...