Psychiatry

Natural language processing to extract symptoms of severe mental illness from clinical text: the Clinical Record Interactive Search Comprehensive Data Extraction (CRIS-CODE) project.

OBJECTIVES: We sought to use natural language processing to develop a suite of language models to capture key symptoms of severe mental illness (SMI) from clinical text, to facilitate the secondary use of mental healthcare data in research.

Effectiveness of Electroconvulsive Therapy Augmentation on Clozapine-Resistant Schizophrenia.

OBJECTIVE: This retrospective case series study of the effectiveness of electroconvulsive therapy (ECT) augmentation on clozapine-resistant schizophrenia was conducted by EMR review.

Cortico-Striatal-Thalamic Loop Circuits of the Salience Network: A Central Pathway in Psychiatric Disease and Treatment.

The salience network (SN) plays a central role in cognitive control by integrating sensory input to guide attention, attend to motivationally salient ...

Medicinal Plants of the Australian Aboriginal Dharawal People Exhibiting Anti-Inflammatory Activity.

Chronic inflammation contributes to multiple ageing-related musculoskeletal and neurodegenerative diseases, cardiovascular diseases, asthma, rheumatoi...

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...

Development of a Machine Learning Algorithm for the Surveillance of Autism Spectrum Disorder.

The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts population-based surveillance of autism spectrum disorder (ASD) among 8-y...

Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia.

Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of...

Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample.

BACKGROUND: Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid sym...

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...

Using clinical information to make individualized prognostic predictions in people at ultra high risk for psychosis.

Recent studies have reported an association between psychopathology and subsequent clinical and functional outcomes in people at ultra-high risk (UHR)...

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 ...

Quantifying Risk for Anxiety Disorders in Preschool Children: A Machine Learning Approach.

Early childhood anxiety disorders are common, impairing, and predictive of anxiety and mood disorders later in childhood. Epidemiological studies over...

Detection of Mild Traumatic Brain Injury by Machine Learning Classification Using Resting State Functional Network Connectivity and Fractional Anisotropy.

Traumatic brain injury (TBI) may adversely affect a person's thinking, memory, personality, and behavior. While mild TBI (mTBI) diagnosis is challengi...

Anesthetic approaches in carotid body tumor surgery.

OBJECTIVE: Carotid body tumors (CBT) are benign tumors that originate from neural non-chromaffin cells that are typically localized near carotid bifur...

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...

EEG and fMRI agree: Mental arithmetic is the easiest form of imagery to detect.

fMRI and EEG during mental imagery provide alternative methods of detecting awareness in patients with disorders of consciousness (DOC) without relian...

A Machine Learning Approach to Identifying the Thought Markers of Suicidal Subjects: A Prospective Multicenter Trial.

Death by suicide demonstrates profound personal suffering and societal failure. While basic sciences provide the opportunity to understand biological ...

Precuneus functioning differentiates first-episode psychosis patients during the fantasy movie Alice in Wonderland.

BACKGROUND: While group-level functional alterations have been identified in many brain regions of psychotic patients, multivariate machine-learning m...

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...