Depression

Machine learning classification of schizophrenia and social anhedonia based on facial expressions.

BACKGROUND AND HYPOTHESIS: Schizophrenia (SCZ) is characterized by deficits in emotional expression, with facial expressions serving as potential markers for diagnosis. Leveraging machine learning and computerized facial analysis, this study aimed to identify facial expression features in patients with SCZ and individuals with high social anhedonia (SocAnh), construct an explainable classification...

NASA's ECOSTRESS satellite reveals widespread midday depression in ecosystem evapotranspiration.

Plants often exhibit a midday depression in water use (i.e., transpiration), reflecting a constraint on their ability to sustain maximum water transport, which may occur at the cost of reduced photosynthesis. Eddy covariance observations and geostationary satellites cannot quantify this widespread phenomenon globally while resolving fine-scale spatial variability. Using evapotranspiration measurem...

Baseline prediction of two-year prevention and remission of anxiety, depression, and eating disorders in college students receiving a digital guided self-help intervention: derivation and external validation of a machine learning algorithm across 26 population-based cohorts.

INTRODUCTION: We examined whether machine learning identified baseline variables that predicted two-year prevention and remission from anxiety, depres...

An Umbrella Review of Artificial Intelligence Applications in Mental Health Care.

BACKGROUND: Artificial intelligence (AI) is increasingly used in mental health care to address rising demand, workforce shortages and access barriers;...

Abnormal gray matter structural covariance networks associated with suicidal ideation in adults with major depressive disorder: Evidence from the REST-meta-MDD consortium.

BACKGROUND: Suicidal ideation (SI) is common in patients with major depressive disorder (MDD) and may represent a clinically meaningful phenotype with...

Association between stomach pain and depression in middle-aged and older chinese adults: Evidence from CHARLS with machine learning and SHAP analysis.

BACKGROUND: Emerging evidence indicates a bidirectional relationship between gastrointestinal symptoms and psychological distress, yet population-base...

A Perovskite Memdiode-Based Neuromorphic in Silico Surrogate Model for Emulating Predictive Coding Failure in Diabetic Neuropathy.

Halide perovskite memdiodes have coupled ionic-electronic dynamics and are promising candidates for artificial synapses in neuromorphic computing. We ...

A Human-Governed Clinical Informatics Framework for Safe AI-Assisted Mental Health Counseling: Secondary Framework Development and Requirement Mapping Study.

BACKGROUND: Natural language processing and large language model systems are increasingly used to support mental health documentation, screening, and ...

Long-term microbiome and clinical effects of a microbiome-guided personalized diet versus low-FODMAP diet in irritable bowel syndrome: A 12-month follow-up randomized controlled trial.

Dietary therapy is central to irritable bowel syndrome (IBS) management, yet the long-term durability of the low-FODMAP diet (LFD), and of microbiome-...

EEG-Based Effective Connectivity for Automated Detection of Major Depressive Disorder.

Major depressive disorder (MDD) is a prevalent mental health condition with profound consequences on daily functioning and quality of life. Existi...

Therapeutic targeting of G protein-coupled receptors in central nervous system disorders: from novel mechanisms to precision pharmacology.

G protein-coupled receptors (GPCRs) are major therapeutic targets for central nervous system disorders, with more than 500 approved drugs targeting th...

Responsible and innovative AI for mental health care: five priority themes.

Artificial intelligence (AI) has entered psychiatry at scale, yet its clinical impact remains constrained by a sizable gap between technical validatio...

Validating objective and scalable speech markers of depression across two independent psychiatric cohorts.

BACKGROUND: Using speech as objective markers for major depressive disorder (MDD) has shown promise, yet their generalizability across clinical settin...

Clinicians' practices and attitudes toward depression assessment: a cross-sectional survey study.

Accurate psychological evaluation is crucial for early detection, intervention and evaluation of mental health disorders. The validity and reliability...

Correlates of physical activity behaviour in a population sample with increased cardiovascular risk and established cardiovascular disease: Cross-sectional analysis of data from the Paracelsus 10,000 prospective cohort study in Salzburg, Austria.

Regular physical activity (PA) remains challenging for many people with high cardiovascular risk and established cardiovascular disease (CVD). We aime...

Connectome-based modeling of the suicidal brain: neurobiological substrates, clinical translation and future perspectives.

Suicide represents a global public health crisis, claiming over 700,000 lives worldwide every year. Deep understanding of the neurobiological mechanis...

Machine learning combined with fMRI identifies dynamic brain network alterations in post-stroke depression: A dual-center cross-sectional study.

OBJECTIVE: Post-stroke depression (PSD) is under-recognized and associated with poorer rehabilitation outcomes and quality of life. We characterized P...

Interpretable Topic Modeling of Spontaneous Speech in Depression Using Large Language Models: Multilingual Four-Cohort Study.

BACKGROUND: Depression is underdiagnosed worldwide, and clinicians rely on interpreting patients' subjective speech. Qualitative analysis of patient l...

Defining 'psychedelic'.

Humphry Osmond coined the term 'psychedelic' in 1956, conjoining 'psyche' for 'soul' and 'delic' for 'to manifest' or 'illuminate'. Soul-illumination ...

Predicting six-year depression trajectories in adulthood: A super learner ensemble approach using the Add Health dataset.

BACKGROUND: Depression is a leading global cause of disability, and much focus has been directed toward identifying population-wide predictors of adul...