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Machine Learning Prediction of Suicide Risk Does Not Identify Patients Without Traditional Risk Factors
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Constructing prediction models and analyzing factors in suicidal ideation using machine learning, focusing on the older population Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies The role of machine learning algorithms in detection of gestational diabetes; a narrative review of current evidence Accuracy and transportability of machine learning models for adolescent suicide prediction with longitudinal clinical records Development and external validation of a logistic and a penalized logistic model using machine-learning techniques to predict suicide attempts: A multicenter prospective cohort study in Korea Leveraging machine learning to enhance postoperative risk assessment in coronary artery bypass grafting patients with unprotected left main disease - A retrospective cohort study Leveraging machine learning to enhance postoperative risk assessment in coronary artery bypass grafting patients with unprotected left main disease - A retrospective cohort study Machine Learning Predicts Unplanned Care Escalations for Post-Anesthesia Care Unit Patients during the Perioperative Period: A Single-Center Retrospective Study Machine Learning-Based Prediction of Helicobacter pylori Infection Study in Adults Precise risk-prediction model including arterial stiffness for new-onset atrial fibrillation using machine learning techniques Emerging Themes and Research Frontiers in Suicide Prediction: A Scientometric Analysis Breaking the silence: leveraging social interaction data to identify high-risk suicide users online using network analysis and machine learning Development and validation of a simple and practical model for early detection of diabetic macular edema in patients with type 2 diabetes mellitus using easily accessible systemic variables Risk factors analysis and prediction model construction for severe pneumonia in older adult patients Pediatric cardiac surgery: machine learning models for postoperative complication prediction Anticipating influential factors on suicide outcomes through machine learning techniques: Insights from a suicide registration program in western Iran Anticipating influential factors on suicide outcomes through machine learning techniques: Insights from a suicide registration program in western Iran Artificial intelligence and machine learning's role in sepsis-associated acute kidney injury BioM2: biologically informed multi-stage machine learning for phenotype prediction using omics data Unravelling psychiatric heterogeneity and predicting suicide attempts in women with trauma-related dissociation using artificial intelligence Suicide prevention Modeling mortality prediction in older adults with dementia receiving COVID-19 vaccination Imaging meningioma biology: Machine learning predicts integrated risk score in WHO grade 2/3 meningioma Machine-Learning Approaches for Risk Prediction in Transcatheter Aortic Valve Implantation: Systematic Review and Meta-Analysis Suicide among patients with oral cancer: A population-based study Understanding and comparing risk factors and subtypes in South Korean adult and adolescent women's suicidal ideation or suicide attempt using survey and social media data Self-Explainable Graph Neural Network for Alzheimer Disease and Related Dementias Risk Prediction: Algorithm Development and Validation Study Self-Explainable Graph Neural Network for Alzheimer Disease and Related Dementias Risk Prediction: Algorithm Development and Validation Study Individual suicide risk factors with resting-state brain functional connectivity patterns in bipolar disorder patients based on latent Dirichlet allocation model Deep learning methods for protein function prediction Predicting the Population Risk of Suicide Using Routinely Collected Health Administrative Data in Quebec, Canada: Model-Based Synthetic Estimation Study Comparison of model feature importance statistics to identify covariates that contribute most to model accuracy in prediction of insomnia Risk factors and prediction model of delirium in elderly patients after hip arthroplasty Risk factors and prediction model of delirium in elderly patients after hip arthroplasty Machine learning-based identification of the risk factors for postoperative nausea and vomiting in adults Predictive model of risk factors for 28-day mortality in patients with sepsis or sepsis-associated delirium based on the MIMIC-IV database Machine learning prediction of hypertension and diabetes in twin pregnancies using characteristics at prenatal care entry: a nationwide study Identifying behaviour-related and physiological risk factors for suicide attempts in the UK Biobank Risk Prediction Model for Non-Suicidal Self-Injury in Chinese Adolescents with Major Depressive Disorder Based on Machine Learning Generating Complex Explanations for Artificial Intelligence Models: An Application to Clinical Data on Severe Mental Illness Can life events predict first-time suicide attempts? A nationwide longitudinal study Can life events predict first-time suicide attempts? A nationwide longitudinal study Transforming Hypertension Diagnosis and Management in The Era of Artificial Intelligence: A 2023 National Heart, Lung, and Blood Institute (NHLBI) Workshop Report Semantic and traditional feature fusion for software defect prediction using hybrid deep learning model Advancements in Artificial Intelligence for Precision Diagnosis and Treatment of Myocardial Infarction: A Comprehensive Review of Clinical Trials and Randomized Controlled Trials Age-stratified predictions of suicide attempts using machine learning in middle and late adolescence Insights Derived From Text-Based Digital Media, in Relation to Mental Health and Suicide Prevention, Using Data Analysis and Machine Learning: Systematic Review Predicting kidney allograft survival with explainable machine learning Chinese expert consensus on pediatric anesthesia assessment and perioperative risk prediction (2024 edition) Machine learning applied to prediction of relapse, hospitalization, and suicide in bipolar disorder using neuroimaging and clinical data: A systematic review Introducing enzymatic cleavage features and transfer learning realizes accurate peptide half-life prediction across species and organs A Systematic Review of Artificial Intelligence Models for Time-to-Event Outcome Applied in Cardiovascular Disease Risk Prediction Age-stratified risk of suicide in patients with schizophrenia Interpretable machine learning model for early prediction of delirium in elderly patients following intensive care unit admission: a derivation and validation study A machine learning tool for identifying patients with newly diagnosed diabetes in primary care Early sepsis mortality prediction model based on interpretable machine learning approach: development and validation study Factors associated with suicide risk and attempts in healthcare students: A cross-sectional study AI-based Fully-Automated Stress Left Ventricular Ejection Fraction as a Prognostic Marker in Patients Undergoing Stress-CMR A model for identifying potentially inappropriate medication used in older people with dementia: a machine learning study Predicting postoperative delirium assessed by the Nursing Screening Delirium Scale in the recovery room for non-cardiac surgeries without craniotomy: A retrospective study using a machine learning approach Predicting who has delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage using machine learning approach: a multicenter, retrospective cohort study ADHD Patients with Suicidal Behaviour: Risk Factors, Comorbidities, and Clinical Profile: A Naturalistic Exploratory Study Cross-Modal Prediction of Spectral and Structural Descriptors via a Pretrained Model Enhanced with Chemical Insights The impact of history of depression and access to weapons on suicide risk assessment: a comparison of ChatGPT-3.5 and ChatGPT-4
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Machine Learning Prediction of Suicide Risk Does Not Identify Patients Without Traditional Risk Factors
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Machine Learning Prediction of Suicide Risk Does Not Identify Patients Without Traditional Risk Factors
🌐 365 Days
AI Virtual Reality Related Evidence Matrix
Predicting suicide risk in real-time crisis hotline chats integrating machine learning with psychological factors: Exploring the black box Constructing prediction models and analyzing factors in suicidal ideation using machine learning, focusing on the older population The use of machine learning on administrative and survey data to predict suicidal thoughts and behaviors: a systematic review Unveiling Adolescent Suicidality: Holistic Analysis of Protective and Risk Factors Using Multiple Machine Learning Algorithms Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies The role of machine learning algorithms in detection of gestational diabetes; a narrative review of current evidence Machine learning in internet financial risk management: A systematic literature review An explainable machine learning model for prediction of high-risk nonalcoholic steatohepatitis Identifying depression in the United States veterans using deep learning algorithms, NHANES 2005-2018 Accuracy and transportability of machine learning models for adolescent suicide prediction with longitudinal clinical records Machine learning-based analysis for prediction of surgical necrotizing enterocolitis in very low birth weight infants using perinatal factors: a nationwide cohort study Investigating Machine Learning Techniques for Predicting Risk of Asthma Exacerbations: A Systematic Review Machine learning-based prediction for self-harm and suicide attempts in adolescents Rethinking Dementia Risk Prediction: A Critical Evaluation of a Multimodal Machine Learning Predictive Model Development and external validation of a logistic and a penalized logistic model using machine-learning techniques to predict suicide attempts: A multicenter prospective cohort study in Korea Leveraging machine learning to enhance postoperative risk assessment in coronary artery bypass grafting patients with unprotected left main disease - A retrospective cohort study Leveraging machine learning to enhance postoperative risk assessment in coronary artery bypass grafting patients with unprotected left main disease - A retrospective cohort study Machine Learning Predicts Unplanned Care Escalations for Post-Anesthesia Care Unit Patients during the Perioperative Period: A Single-Center Retrospective Study Machine Learning-Based Prediction of Helicobacter pylori Infection Study in Adults Machine learning techniques in diagnostics and prediction of the clinical features of schizophrenia: a narrative review Precise risk-prediction model including arterial stiffness for new-onset atrial fibrillation using machine learning techniques Suicide risk assessment tools and prediction models: new evidence, methodological innovations, outdated criticisms Emerging Themes and Research Frontiers in Suicide Prediction: A Scientometric Analysis Breaking the silence: leveraging social interaction data to identify high-risk suicide users online using network analysis and machine learning Development and validation of a simple and practical model for early detection of diabetic macular edema in patients with type 2 diabetes mellitus using easily accessible systemic variables Suicide attempt risk predicts inconsistent self-reported suicide attempts: A machine learning approach using longitudinal data Risk factors analysis and prediction model construction for severe pneumonia in older adult patients Machine learning approaches for practical predicting outpatient near-future AECOPD based on nationwide electronic medical records Machine learning approaches for practical predicting outpatient near-future AECOPD based on nationwide electronic medical records Artificial Intelligence-Derived Risk Prediction: A Novel Risk Calculator Using Office and Ambulatory Blood Pressure Machine Learning for prediction of violent behaviors in schizophrenia spectrum disorders: a systematic review Pediatric cardiac surgery: machine learning models for postoperative complication prediction Evidence for the biopsychosocial model of suicide: a review of whole person modeling studies using machine learning Predicting ischemic stroke patients' prognosis changes using machine learning in a nationwide stroke registry Machine Learning-Based Prediction of Suicidality in Adolescents With Allergic Rhinitis: Derivation and Validation in 2 Independent Nationwide Cohorts Anticipating influential factors on suicide outcomes through machine learning techniques: Insights from a suicide registration program in western Iran Anticipating influential factors on suicide outcomes through machine learning techniques: Insights from a suicide registration program in western Iran Machine Learning as a Diagnostic and Prognostic Tool for Predicting Thrombosis in Cancer Patients: A Systematic Review Risk factors of suicide re-attempt: A two-year prospective study Development and validation of a machine learning model for prediction of type 2 diabetes in patients with mental illness Machine Learning-Based Prediction of Suicidal Thinking in Adolescents by Derivation and Validation in 3 Independent Worldwide Cohorts: Algorithm Development and Validation Study Artificial intelligence and machine learning's role in sepsis-associated acute kidney injury BioM2: biologically informed multi-stage machine learning for phenotype prediction using omics data Detection of Suicidal Ideation in Clinical Interviews for Depression Using Natural Language Processing and Machine Learning: Cross-Sectional Study Suicide Attempts in Patients With Amyotrophic Lateral Sclerosis: An Analysis of the Korean National Health Insurance Database Developing a risk prediction model for death at first suicide attempt-Identifying risk factors from Thailand's national suicide surveillance system data Identifying suicide attempter in major depressive disorder through machine learning: the importance of pain avoidance, event-related potential features of affective processing Unravelling psychiatric heterogeneity and predicting suicide attempts in women with trauma-related dissociation using artificial intelligence Suicide prevention Modeling mortality prediction in older adults with dementia receiving COVID-19 vaccination Prediction of dementia based on older adults' sleep disturbances using machine learning Predicting Treatment Outcome Based on Resting-State Functional Connectivity in Internalizing Mental Disorders: A Systematic Review and Meta-Analysis Benchmarking clinical risk prediction algorithms with ensemble machine learning for the non-invasive diagnosis of liver fibrosis in NAFLD Prevalence and correlates of suicide risk among non-psychiatric inpatients in a general hospital in China Machine learning in the prediction and detection of new-onset atrial fibrillation in ICU: a systematic review Imaging meningioma biology: Machine learning predicts integrated risk score in WHO grade 2/3 meningioma Machine-Learning Approaches for Risk Prediction in Transcatheter Aortic Valve Implantation: Systematic Review and Meta-Analysis Long-Term Survival Prediction Model for Elderly Community Members Using a Deep Learning Method Suicide among patients with oral cancer: A population-based study Adolescent, Parent, and Provider Perceptions of a Predictive Algorithm to Identify Adolescent Suicide Risk in Primary Care On mental pain and suicide risk in modern psychiatry Applications of Artificial Intelligence Methods for the Prediction of Osteoporotic Fractures Understanding and comparing risk factors and subtypes in South Korean adult and adolescent women's suicidal ideation or suicide attempt using survey and social media data Risk factors of reattempt among suicide attempters in South Korea: A nationwide retrospective cohort study