Psychiatry

Machine learning models for detecting suicidal ideation in Chinese in-patients with major depressive disorder: A single-centre retrospective study.

UNLABELLED: Suicide claims >720,000 lives annually; major depressive disorder (MDD) carries the highest population-attributable risk. Suicidal ideation (SI), the most proximal modifiable predictor of attempt,is poorly captured by subjective scales. We developed and internally validated machine-learning models to detect SI in Chinese MDD in-patients using routine electronic medical records. PURPOSE...

Predicting suicidal ideation from depression screening data: A network-augmented machine learning approach.

BACKGROUND: Suicidal ideation is often assessed using a single self-report item in routine screening. We developed a model that combines machine learning with symptom-network analytics to infer an auxiliary signal relevant to suicidal ideation from routine depressive-symptom data. METHODS: Adults from the National Health and Nutrition Examination Survey (N = 44,922) were used to predict ideation (...

Altered brain network topology in adolescents with major depressive disorder and bipolar disorder: A resting-state fMRI graph-theoretical and machine learning study.

BACKGROUND: Adolescents with major depressive disorder (MDD) and bipolar disorder (BD) share substantial clinical overlap and elevated suicide risk, y...

Multi-domain ECG feature extraction enable accurate automated recognition of bipolar disorder, depression and schizophrenia.

OBJECTIVE: To develop and validate a multi-lead electrocardiogram (ECG)-based machine learning system for automated classification of major psychiatri...

Artificial intelligence perceptions and career anxiety among health sciences students.

Recent rapid developments in artificial intelligence (AI) technologies are leading to significant changes in social and economic structures. These cha...

Deep learning using electroencephalogram (EEG) data for diagnosing and predicting SSRI response in major depressive disorder.

BACKGROUND: Major Depression (MDD) is a potentially life-threatening condition that ranks among the diseases with the highest global burden. Despite i...

Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data.

Severe coronavirus disease 2019 (COVID-19) has posed ongoing clinical and public health challenges worldwide, with Korea providing a unique perspectiv...

Predicting early clinical recovery in first-episode psychosis: development and external validation of a clinically interpretable multivariable model.

BACKGROUND: Identifying patients with first-episode psychosis (FEP) who are unlikely to achieve early clinical recovery (ECR) is critical for personal...

REM Sleep Abnormalities in Children With Autism Spectrum Disorder.

Sleep disturbances are common in children with autism spectrum disorder (ASD). However, the sleep pattern changes including rapid eye movement (REM) s...

Assessing the accuracy of 4 generative AI tools to guide dosing of long-acting injectable antipsychotics.

PURPOSE: The purpose of this study was to review the accuracy of 4 different artificial intelligence (AI) tools in providing dosing recommendations fo...

Clinical judgment: an essential method in medicine.

Physicians rely on clinical judgment and patients look for it. However, clinical judgment is infrequently discussed in the literature, and is often pe...

Differentiating Depression Subtypes through three-electrode EEG and Emotional Stimuli: A Machine Learning Approach.

We propose an EEG-based framework for depression subtype assessment using emotion-modulated neural dynamics elicited by immersive virtual reality (VR)...

A Deep Learning Approach for Analyzing Brainwave Signals During Audio Meditation in Expectant Mothers: Variational Mode Decomposition with a CNN-BiLSTM Model.

Meditation has increasingly been recognized as a helpful non-pharmacological intervention to treat psychological stress, anxiety, and depression durin...

Identifying postpartum depression subtypes using natural language processing and clinical notes.

BACKGROUND: Postpartum depression (PPD) remains vastly underdiagnosed, and its clinical heterogeneity is not well understood. Diagnosis codes in elect...

Explicitly acquired interrelations among mental schema reduces cognitive load and facilitates emergence of novel responses in mice and artificial neural networks.

Mammalian brain has evolved to infer from past experiences and elicit context relevant novel behavioural responses hitherto unexpressed by the animal....

Attitudes toward artificial intelligence among individuals with anxiety, depression, bipolar disorders, and schizophrenia.

BACKGROUND: Artificial intelligence (AI) increasingly supports medical diagnosis, interventions, and clinical decision-making. In various domains of h...

Nurses' artificial intelligence anxiety levels, their attitudes towards artificial intelligence, and their skills in acting humanistically in nursing practices.

AIM: This study aims to investigate the levels of artificial intelligence-related anxiety among nurses, their attitudes towards the use of AI in clini...

Digital and artificial intelligence literacy in inflammatory rheumatic and degenerative joint diseases.

PURPOSE: The development of digital technologies and artificial intelligence (AI) in healthcare has highlighted the need for patients to improve digit...

A Therapeutic Conversational Agent (Solace) for Management of Chronic Pain: Acceptability and Usability Study.

BACKGROUND: Chronic pain is a critical cause of personal suffering and societal concern. However, treatment options remain inadequate, and access to e...

Exploring brain lobe-specific insights in an explainable framework for EEG-based schizophrenia detection.

Schizophrenia (ScZ) is a growing global health concern that affects millions of people and puts severe pressure on healthcare systems. Early detection...