machine learning
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antipsychotic, BMJ Mental Health, cardiovascular disease, cardiovascular events, cohort study, Denmark, Editor Eimear Foley, electronic health records, external validation, health inequalities, lasso regression, logistic regression, machine learning, mixed methods, mortality gap, physical health, physical health inequalities, prediction, psychosis, registry data, risk factors, risk prediction, schizophrenia, Sweden, topical, xgboostPredicting cardiovascular disease in schizophrenia: does machine learning actually help?
On average, people with schizophrenia spectrum disorders die 15 to 20 years…
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antipsychotic, BMJ Mental Health, cardiovascular disease, cardiovascular events, cohort study, Denmark, Editor Eimear Foley, electronic health records, external validation, health inequalities, lasso regression, logistic regression, machine learning, mixed methods, mortality gap, physical health, physical health inequalities, prediction, psychosis, registry data, risk factors, risk prediction, schizophrenia, Sweden, topical, xgboostPredicting cardiovascular disease in schizophrenia: does machine learning actually help?
On average, people with schizophrenia spectrum disorders die 15 to 20 years…
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A4 study, ADNI, Alzheimer’s disease, amyloid PET, blood biomarker, Brain, calibration, cognition, machine learning, negative predictive value, Neurodegenerative Diseases, p-tau217, plasma biomarkersAlzheimer’s Blood Biomarker Models Lose Rule-Out Power Across Cohorts
A 2026 ADNI/A4 validation study found that Alzheimer’s plasma-biomarker machine-learning models still…
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Anxiety, app engagement, digital mental health, digital mindfulness, generalized anxiety disorder, machine learning, meditation, mindfulness ecological momentary intervention, Psychiatry, Psychology, random forest, self-monitoring, SHAP, therapy, treatment matchingDigital Mindfulness for GAD: Machine Learning Predicted App Engagement
A 2026 machine-learning analysis of 110 adults with generalized anxiety disorder predicted…
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ADNI, Alzheimer’s disease, ANA-GNN, artificial-intelligence, Brain, clinical decision support, cognition, dementia diagnosis, graph neural network, hippocampus, machine learning, mild cognitive impairment, Neurodegenerative Diseases, neuroimaging, neuroscience, posterior cingulate cortex, structural MRIAlzheimer’s AI MRI Diagnosis: ANA-GNN Reaches 85.23% Accuracy in ADNI
A 2026 ADNI study reported 85.23% accuracy for ANA-GNN, a graph neural…
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auditory neuroscience, Brain, CatBoost, gaba, lipidomics, machine learning, metabolomics, neuroscience, noise exposure, occupational noise, Psychiatry, Psychology, serum biomarkers, sphingolipids, Th1 inflammation, tinnitusNoise Exposure Tinnitus Biomarkers: 92% Metabolite Mediation
A 2026 serum multiomics study linked occupational noise exposure to tinnitus severity…
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AI screening, algorithmic fairness, AUPRC, clinical decision support, machine learning, Maryland Suicide Data Warehouse, positive predictive value, precision recall, Psychiatry, Psychology, suicide, suicide risk, xgboostXGBoost Suicide Risk Model Reached 96% PPV at Top 0.1% Threshold
A 2026 Scientific Reports study of Maryland suicide-death records found that an…
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area under the curve, artificial-intelligence, Best Linear Unbiased Prediction, Biological Psychiatry, brain imaging, cerebellum, cortex, deep-learning, DEP-ARREST CLIN, depression, Editor Eimear Foley, ENIGMA MDD consortium, hippocampus, machine learning, neuroimaging, polygenic scores, region-of-interest analysis, subcortical structures, topical, Translational PsychiatryBrain scans, depression, and AI: small signals, big questions
The World Health Organization (WHO) projects that by 2030, major depressive disorder…
