xgboost
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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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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…
