Bipolar Disorder

High-throughput transformation of Saccharomyces cerevisiae using liquid handling robots.

Saccharomyces cerevisiae (budding yeast) is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc) transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids) or genome mutation (e.g.,...

A symptom network structure of the psychosis spectrum.

Current diagnostic systems mainly focus on symptoms needed to classify patients with a specific mental disorder and do not take into account the variation in co-occurring symptoms and the interaction between the symptoms themselves. The innovative network approach aims to further our understanding of mental disorders by focusing on meaningful connections between individual symptoms of a disorder a...

Diagnosis of major depressive disorder by combining multimodal information from heart rate dynamics and serum proteomics using machine-learning algorithm.

OBJECTIVE: Major depressive disorder (MDD) is a systemic and multifactorial disorder that involves abnormalities in multiple biochemical pathways and ...

Construction of longitudinal prediction targets using semisupervised learning.

In establishing prognostic models, often aided by machine learning methods, much effort is concentrated in identifying good predictors. However, the s...

A Novel Sensitive Method to Measure Catechol-O-Methyltransferase Activity Unravels the Presence of This Activity in Extracellular Vesicles Released by Rat Hepatocytes.

There is a clear need for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and r...

Predictive diagnosis of major depression using NMR-based metabolomics and least-squares support vector machine.

BACKGROUND: Major depressive (MD) disorder is a serious psychiatric disorder that can result in suicidal behavior if not treated. The MD diagnosis usi...

MoSe Nanolabels for Electrochemical Immunoassays.

There is huge interest in biosensors as a result of the demand for personalized medicine. In biomolecular detection, transition-metal dichalcogenides ...

Determining Fuzzy Membership for Sentiment Classification: A Three-Layer Sentiment Propagation Model.

Enormous quantities of review documents exist in forums, blogs, twitter accounts, and shopping web sites. Analysis of the sentiment information hidden...

Targeted use of growth mixture modeling: a learning perspective.

From the statistical learning perspective, this paper shows a new direction for the use of growth mixture modeling (GMM), a method of identifying late...

A support vector machine model provides an accurate transcript-level-based diagnostic for major depressive disorder.

Major depressive disorder (MDD) is a critical cause of morbidity and disability with an economic cost of hundreds of billions of dollars each year, ne...

Predicting early psychiatric readmission with natural language processing of narrative discharge summaries.

The ability to predict psychiatric readmission would facilitate the development of interventions to reduce this risk, a major driver of psychiatric he...

Artificial neural network EMG classifier for functional hand grasp movements prediction.

Objective To design and implement an electromyography (EMG)-based controller for a hand robotic assistive device, which is able to classify the user's...

Towards person-centered neuroimaging markers for resilience and vulnerability in Bipolar Disorder.

Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals i...

Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations.

Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often co...

Accuracy of automated classification of major depressive disorder as a function of symptom severity.

BACKGROUND: Growing evidence documents the potential of machine learning for developing brain based diagnostic methods for major depressive disorder (...

Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.

Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding...

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modal...

Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning.

Diagnosis, clinical management and research of psychiatric disorders remain subjective - largely guided by historically developed categories which may...

Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders.

Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these...

Does lower urine-specific gravity predict decline in renal function and hypernatremia in older adults exposed to psychotropic medications? An exploratory analysis.

BACKGROUND: Exposure to psychotropic agents, including lithium, antipsychotics and antidepressants, has been associated with nephrogenic diabetes insi...