Depression

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...

Reflections of Low-Income, Second-Generation Latinas About Experiences in Depression Therapy.

Depression is higher among second-generation Latinas compared with immigrants, but mental health tre...

Cross-trial prediction of treatment outcome in depression: a machine learning approach.

BACKGROUND: Antidepressant treatment efficacy is low, but might be improved by matching patients to ...

Identifying a clinical signature of suicidality among patients with mood disorders: A pilot study using a machine learning approach.

OBJECTIVE: A growing body of evidence has put forward clinical risk factors associated with patients...

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, ...

Studying depression using imaging and machine learning methods.

Depression is a complex clinical entity that can pose challenges for clinicians regarding both accur...

Analyzing depression tendency of web posts using an event-driven depression tendency warning model.

OBJECTIVE: The Internet has become a platform to express individual moods/feelings of daily life, wh...

MDD-SOH: exploiting maximal dependence decomposition to identify S-sulfenylation sites with substrate motifs.

UNLABELLED: S-sulfenylation (S-sulphenylation, or sulfenic acid), the covalent attachment of S-hydro...

Antidepressant use in late gestation and risk of postpartum haemorrhage: a retrospective cohort study.

OBJECTIVE: To investigate the association between antidepressant use in late gestation and postpartu...