Bipolar Disorder

Hybrid Recommender System for Mental Illness Detection in Social Media Using Deep Learning Techniques.

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...

Interval-valued bipolar fuzzy line graphs.

OBJECTIVES: The notion of Bipolarity based on positive and negative outcomes. It is well known that bipolar models give more precision, flexibility, and compatibility to the system as compared to the classical models and fuzzy models. A bipolar fuzzy graph(BFG) provides more flexibility while modeling human thinking as compared with a fuzzy graph, and an interval valued bipolar fuzzy graph(IVBFG) ...

Tool-tissue force segmentation and pattern recognition for evaluating neurosurgical performance.

Surgical data quantification and comprehension expose subtle patterns in tasks and performance. Enabling surgical devices with artificial intelligence...

Bipolar intuitionistic fuzzy graph based decision-making model to identify flood vulnerable region.

Bipolar intuitionistic fuzzy graphs (BIFG) are an extension of fuzzy graphs that can effectively capture uncertain or imprecise information in various...

Black-box assisted medical decisions: AI power vs. ethical physician care.

I raise an ethical problem with physicians using "black box" medical AI algorithms, arguing that its use would compromise proper patient care. Even if...

A CMOS Temperature Sensor with a Smart Calibrated Inaccuracy of ±0.11 (3σ).

This paper presents a BJT-based smart CMOS temperature sensor. The analog front-end circuit contains a bias circuit and a bipolar core; the data conve...

Reorienting Latent Variable Modeling for Supervised Learning.

Despite its potentials benefits, using prediction targets generated based on latent variable (LV) modeling is not a common practice in supervised lear...

Identifying the Influencing Factors of Depressive Symptoms among Nurses in China by Machine Learning: A Multicentre Cross-Sectional Study.

BACKGROUND: Nurses' high workload can result in depressive symptoms. However, the research has underexplored the internal and external variables, such...

Design of continuous-time recurrent neural networks with piecewise-linear activation function for generation of prescribed sequences of bipolar vectors.

A recurrent neural network (RNN) can generate a sequence of patterns as the temporal evolution of the output vector. This paper focuses on a continuou...

Chronic Stress Exposure Alters the Gut Barrier: Sex-Specific Effects on Microbiota and Jejunum Tight Junctions.

BACKGROUND: Major depressive disorder (MDD) is the leading cause of disability worldwide. Of individuals with MDD, 30% to 50% are unresponsive to comm...

CG02N Analyzer Accurately Measures Fibrinogen Level in Whole Blood in the Presence of Low- or High-Dose Heparin.

Rapid fibrinogen (Fbg) evaluation is important in patients with massive bleeding during severe trauma and those undergoing major surgery. However, the...

Prevalence of depressive symptoms and associated factors during the COVID-19 pandemic: A national-based study.

BACKGROUND: Previous studies have reported that the prevalence of depression and depressive symptoms was significantly higher than that before the COV...

Ultrastretchable High-Conductivity MXene-Based Organohydrogels for Human Health Monitoring and Machine-Learning-Assisted Recognition.

Conductive hydrogels as promising candidates of wearable electronics have attracted considerable interest in health monitoring, multifunctional electr...

Optimizing multi-domain hematologic biomarkers and clinical features for the differential diagnosis of unipolar depression and bipolar depression.

There is a lack of objective features for the differential diagnosis of unipolar and bipolar depression, especially those that are readily available i...

Evaluation of boundaries between mood and psychosis disorder using dynamic functional network connectivity (dFNC) via deep learning classification.

The validity and reliability of diagnoses in psychiatry is a challenging topic in mental health. The current mental health categorization is based pri...

Uncovering psychiatric phenotypes using unsupervised machine learning: A data-driven symptoms approach.

BACKGROUND: Current categorical classification systems of psychiatric diagnoses lead to heterogeneity of symptoms within disorders and common co-occur...

Identifying suicide attempts, ideation, and non-ideation in major depressive disorder from structural MRI data using deep learning.

The present study aims to identify suicide risks in major depressive disorders (MDD) patients from structural MRI (sMRI) data using deep learning. In ...

Biphasic burst and sustained transdermal delivery in vivo using an AI-optimized 3D-printed MN patch.

The objective of the present study was to fabricate microneedles for delivering lipophilic active ingredients (APIs) using digital light processing (D...

Cognitive Depression Detection Cyber-Medical System Based on EEG Analysis and Deep Learning Approaches.

Long-term depression and negative emotional cycles affect life quality and work productivity. However, depression is not easy to detect, with current ...

The assistance of BAZAR robot promotes improved upper limb motor coordination in workers performing an actual use-case manual material handling.

This study aims at evaluating upper limb muscle coordination and activation in workers performing an actual use-case manual material handling (MMH). T...