Bipolar Disorder

A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability.

The post-effects of the COronaVIrus Disease (COVID-19) vary depending on socioeconomic and biological factors. Similarly, the effects of vaccination on people's immunity vary across several factors. After the pandemic, real-life post-vaccination anomalies significantly impact women's health, access to medical treatments and medications, mental well-being, and daily physical activities. However, th...

An integrated machine learning framework for developing and validating a diagnostic model of major depressive disorder based on interstitial cystitis-related genes.

BACKGROUND: Major depressive disorder (MDD) and interstitial cystitis (IC) are two highly debilitating conditions that often coexist with reciprocal effect, significantly exacerbating patients' suffering. However, the molecular underpinnings linking these disorders remain poorly understood.

A machine-learning approach to model risk and protective factors of vulnerability to depression.

There are multiple risk and protective factors for depression. The association between these factors with vulnerability to depression is unclear. Such...

Predictive Models for Suicide Attempts in Major Depressive Disorder and the Contribution of : A Pilot Integrative Machine Learning Study.

Suicide is a major public health problem caused by a complex interaction of various factors. Major depressive disorder (MDD) is the most prevalent psy...

Twenty-four-hour physical activity patterns associated with depressive symptoms: a cross-sectional study using big data-machine learning approach.

BACKGROUND: Depression is a global burden with profound personal and economic consequences. Previous studies have reported that the amount of physical...

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning.

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatme...

3D-printed portable device for illicit drug identification based on smartphone-imaging and artificial neural networks.

In this manuscript, a 3D-printed analytical device has been successfully developed to classify illicit drugs using smartphone-based colorimetry. Repre...

Spectral Graph Neural Network-Based Multi-Atlas Brain Network Fusion for Major Depressive Disorder Diagnosis.

Major Depressive Disorder (MDD) imposes a substantial burden within the healthcare domain, impacting millions of individuals worldwide. Functional Mag...

How can industrial intelligence change the employment structure of the floating population?

As the wave of industrial intelligence (AI) swept, the demographic dividend era in the Chinese labor market continued to decrease. This study aimed to...

The Contribution of Explainable Machine Learning Algorithms Using ROI-based Brain Surface Morphology Parameters in Distinguishing Early-onset Schizophrenia From Bipolar Disorder.

RATIONALE AND OBJECTIVES: To differentiate early-onset schizophrenia (EOS) from early-onset bipolar disorder (EBD) using surface-based morphometry mea...

Emergency department risk model: timely identification of patients for outpatient care coordination.

OBJECTIVE: Major depressive disorder (MDD) is linked to a 61% increased risk of emergency department (ED) visits and frequent ED usage. Collaborative ...

The therapeutic effectiveness of artificial intelligence-based chatbots in alleviation of depressive and anxiety symptoms in short-course treatments: A systematic review and meta-analysis.

BACKGROUND: The emergence of artificial intelligence-based chatbot has revolutionized the field of clinical psychology and psychotherapy, granting ind...

Intelligent classification of major depressive disorder using rs-fMRI of the posterior cingulate cortex.

Major Depressive Disorder (MDD) is a widespread psychiatric condition that affects a significant portion of the global population. The classification ...

An Artificial LiSiO Nociceptor with Neural Blockade and Self-Protection Abilities.

An artificial nociceptor, as a critical and special bionic receptor, plays a key role in a bioelectronic device that detects stimuli and provides warn...

Validation of Machine Learning-Based Assessment of Major Depressive Disorder from Paralinguistic Speech Characteristics in Routine Care.

New developments in machine learning-based analysis of speech can be hypothesized to facilitate the long-term monitoring of major depressive disorder ...

Identification of depressive symptoms: A cause-and-effect based machine learning study.

Implementation of Learning Management Systems (LMS) in higher education systems through bipolar complex hesitant fuzzy Aczel-Alsina power aggregation operators: A case review for China.

A learning management system (LMS) is a web-based application or software platform computed to facilitate the development, tracking, management, repor...

BPI-GNN: Interpretable brain network-based psychiatric diagnosis and subtyping.

Converging evidence increasingly suggests that psychiatric disorders, such as major depressive disorder (MDD) and autism spectrum disorder (ASD), are ...

A machine learning based depression screening framework using temporal domain features of the electroencephalography signals.

Depression is a serious mental health disorder affecting millions of individuals worldwide. Timely and precise recognition of depression is vital for ...

Machine-based learning of multidimensional data in bipolar disorder - pilot results.

INTRODUCTION: Owing to the heterogenic picture of bipolar disorder, it takes approximately 8.8 years to reach a correct diagnosis. Early recognition a...