Depression

Antidepressant-like effects of Gan-Mai-Dazao-Tang via monoamine regulatory pathways on forced swimming test in rats.

Depression is a highly prevalent and recurrent mental disorder that impacts all aspects of human lif...

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 a...

Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study.

BACKGROUND: Generalized anxiety disorder (GAD) is difficult to recognize and hard to separate from m...

Effectiveness of Electroconvulsive Therapy Augmentation on Clozapine-Resistant Schizophrenia.

OBJECTIVE: This retrospective case series study of the effectiveness of electroconvulsive therapy (E...

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 ...

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. Identific...

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 suic...

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 func...

A case of central diabetes insipidus after ketamine infusion during an external to internal carotid artery bypass.

STUDY OBJECTIVE: We report the first teenage case of ketamine-induced transient central diabetes ins...

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...

Why so GLUMM? Detecting depression clusters through graphing lifestyle-environs using machine-learning methods (GLUMM).

BACKGROUND: Key lifestyle-environ risk factors are operative for depression, but it is unclear how r...

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 cos...

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 ...

Physicochemical stability of oxycodone-ketamine solutions in polypropylene syringe and polyvinyl chloride bag for patient-controlled analgesia use.

OBJECTIVES: The study evaluated the stability of three combinations of oxycodone and ketamine dilute...

Does an interaction exist between ketamine hydrochloride and Becton Dickinson syringes?

INTRODUCTION: An international alert from Becton Dickinson (BD) has noted the possibility of interac...

Novel Use of Natural Language Processing (NLP) to Predict Suicidal Ideation and Psychiatric Symptoms in a Text-Based Mental Health Intervention in Madrid.

Natural language processing (NLP) and machine learning were used to predict suicidal ideation and he...

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 ...

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 ...

Non-reward neural mechanisms in the orbitofrontal cortex.

Single neurons in the primate orbitofrontal cortex respond when an expected reward is not obtained, ...

Letter to the Editor: Suicide as a complex classification problem: machine learning and related techniques can advance suicide prediction - a reply to Roaldset (2016).

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have p...