Latest AI and machine learning research in psychiatry for healthcare professionals.
Electroencephalograms (EEG) is used to assess patients' clinical records of depression (EEG). The disorder of human thinking is a very complex problem caused by heavy-duty in daily life. We need some future and optimal classifier selection by using different techniques for depression data extraction using EEG. Intelligent decision support is a decision-making process that is automated based on som...
Recommender systems are chiefly renowned for their applicability in e-commerce sites and social media. For system optimization, this work introduces a method of behaviour pattern mining to analyze the person's mental stability. With the utilization of the sequential pattern mining algorithm, efficient extraction of frequent patterns from the database is achieved. A candidate sub-sequence generatio...
Because there are a limited number of animal models for psychiatric diseases that can be extrapolated to humans, drug repurposing has been actively pu...
OBJECTIVES: The notion of Bipolarity based on positive and negative outcomes. It is well known that bipolar models give more precision, flexibility, a...
With the continuous development of society, people's life pressure is constantly increasing, and the mental health problems of college students are be...
INTRODUCTION: Psychiatric disorders are a leading cause of disability worldwide, calling for an urgent need for new treatments, early detection, early...
BACKGROUND: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders characterized by difficulty communicating with society and oth...
Based on MPP database, we have conducted research and investigation on big data processing and analysis, and provided a good solution for big data. Ho...
The use of deep neural networks for electroencephalogram (EEG) classification has rapidly progressed and gained popularity in recent years, but automa...
In this editorial, we discuss how the diffusion of Artificial Intelligence (AI)-based tools-such as the recently available conversational AIs-could im...
Suicide risk prediction models frequently rely on structured electronic health record (EHR) data, including patient demographics and health care usag...
Fuzzy membership is an effective approach used in twin support vector machines (SVMs) to reduce the effect of noise and outliers in classification pro...
A mixed-methods approach was used to assess the fidelity of virtual environments as ergonomic assessment tools for human-robot interaction. Participan...
Surgical data quantification and comprehension expose subtle patterns in tasks and performance. Enabling surgical devices with artificial intelligence...
PURPOSE: This work aimed to study postpartum mental outcomes and determinants of the intake of caffeinated beverages during the pandemic in women from...
BACKGROUND: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, propos...
Brain-computer interfaces are used for direct two-way communication between the human brain and the computer. Brain signals contain valuable informati...
Bipolar intuitionistic fuzzy graphs (BIFG) are an extension of fuzzy graphs that can effectively capture uncertain or imprecise information in various...
Attention deficit hyperactivity disorder (ADHD) is considered one of the most common psychiatric disorders in childhood. The incidence of this disease...
BACKGROUND: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A ...