Psychiatry

Machine learning studies on major brain diseases: 5-year trends of 2014-2018.

In the recent 5 years (2014-2018), there has been growing interest in the use of machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic lesion changes within the area of neuroradiology. However, to date, the majority of research trend and current status have not been clearly illuminated in the neuroradiology field. More than 1000 papers have been published during ...

Hyponatremia Presenting with Recurrent Mania.

Primary psychogenic polydipsia (PPD) is a chronic, relapsing condition in which there is a disturbance in thirst control primarily due to an underlying disorder such as a psychogenic condition. It is characterized by an increase of fluid intake along with excretion of excessive amounts of dilute urine exceeding 40 to 50 mL/kg of body weight. PPD is typically seen in patients with schizophrenic sym...

Mobile detection of autism through machine learning on home video: A development and prospective validation study.

BACKGROUND: The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to compl...

Toward Automatic Risk Assessment to Support Suicide Prevention.

Suicide has been considered an important public health issue for years and is one of the main causes of death worldwide. Despite prevention strategie...

Supervised machine learning to decipher the complex associations between neuro-immune biomarkers and quality of life in schizophrenia.

Stable phase schizophrenia is characterized by altered patterning in tryptophan catabolites (TRYCATs) and memory impairments, which are associated wit...

Identifying probable post-traumatic stress disorder: applying supervised machine learning to data from a UK military cohort.

BACKGROUND: Early identification of probable post-traumatic stress disorder (PTSD) can lead to early intervention and treatment.

The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review.

BACKGROUND: Machine learning techniques offer promise to improve suicide risk prediction. In the current systematic review, we aimed to review the exi...

Automated Extraction of Diagnostic Criteria From Electronic Health Records for Autism Spectrum Disorders: Development, Evaluation, and Application.

BACKGROUND: Electronic health records (EHRs) bring many opportunities for information utilization. One such use is the surveillance conducted by the C...

Predominant polarity classification and associated clinical variables in bipolar disorder: A machine learning approach.

BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder characterized by periodic episodes of manic and depressive symptomatology. Predomin...

Artificial Intelligence in Radiology: Current Technology and Future Directions.

Artificial intelligence (AI) has been heralded as the next big wave in the computing revolution and touted as a transformative technology for many ind...

A machine learning ensemble to predict treatment outcomes following an Internet intervention for depression.

BACKGROUND: Some Internet interventions are regarded as effective treatments for adult depression, but less is known about who responds to this form o...

Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach.

Many variables have been linked to different course trajectories of depression. These findings, however, are based on group comparisons with unknown t...

Social robots to support children's well-being under medical treatment: A systematic state-of-the-art review.

Hospitalization is a stressful experience for children. Socially assistive robots (SARs), designed to interact with humans, might be a means to mitiga...

Ensemble machine learning prediction of posttraumatic stress disorder screening status after emergency room hospitalization.

Posttraumatic stress disorder (PTSD) develops in a substantial minority of emergency room admits. Inexpensive and accurate person-level assessment of ...

Comparative Evaluation of Machine Learning Strategies for Analyzing Big Data in Psychiatry.

The requirement of innovative big data analytics has become a critical success factor for research in biological psychiatry. Integrative analyses acro...

Feasibility and Acceptability of Mobile Phone-Based Auto-Personalized Physical Activity Recommendations for Chronic Pain Self-Management: Pilot Study on Adults.

BACKGROUND: Chronic pain is a globally prevalent condition. It is closely linked with psychological well-being, and it is often concomitant with anxie...

Individualized prediction of dispositional worry using white matter connectivity.

BACKGROUND: Excessive worry is a defining feature of generalized anxiety disorder and is present in a wide range of other psychiatric conditions. Ther...

Psychiatric stressor recognition from clinical notes to reveal association with suicide.

Suicide takes the lives of nearly a million people each year and it is a tremendous economic burden globally. One important type of suicide risk facto...

Assessing the severity of positive valence symptoms in initial psychiatric evaluation records: Should we use convolutional neural networks?

BACKGROUND AND OBJECTIVE: Efficiently capturing the severity of positive valence symptoms could aid in risk stratification for adverse outcomes among ...

Multi-Channel Convolutional Neural Networks Architecture Feeding for Effective EEG Mental Tasks Classification.

Mental tasks classification is increasingly recognized as a major challenge in the field of EEG signal processing and analysis. State-of-the-art appro...