AIMC Topic: Risk Factors

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Using Machine Learning to Identify Suicide Risk: A Classification Tree Approach to Prospectively Identify Adolescent Suicide Attempters.

Archives of suicide research : official journal of the International Academy for Suicide Research Jun 10, 2019
This study applies classification tree analysis to prospectively identify suicide attempters among a large adolescent community sample, to demonstrate the strengths and limitations of this approach for risk identification. Data were drawn from the Na...
Adolescent Humans Longitudinal Studies Machine Learning Impulsive Behavior Personality Assessment Female Risk Factors Male Risk Assessment Suicide, Attempted
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Artificial neural network optimizes self-examination of osteoporosis risk in women.

The Journal of international medical research Jun 10, 2019
OBJECTIVE: This study aimed to investigate the application of an artificial neural network (ANN) in optimizing the Osteoporosis Self-Assessment Tool for Asians (OSTA) score.
Self-Examination Neural Networks, Computer Middle Aged Female Risk Assessment Prognosis Humans Risk Factors Follow-Up Studies Bone Density Aged Absorptiometry, Photon Osteoporosis Aged, 80 and over
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Machine learning approaches for risk assessment of peripherally inserted Central catheter-related vein thrombosis in hospitalized patients with cancer.

International journal of medical informatics Jun 7, 2019
OBJECTIVE: The aim of this study was to conduct an effective assessment of peripherally inserted central venous catheter (PICC)-related thrombosis based on machine learning (ML) techniques considering genotype.
Humans Machine Learning Prospective Studies Risk Factors Catheterization, Peripheral Catheterization, Central Venous Thrombosis Hospitalization Risk Assessment Neoplasms China
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Prediction models for high risk of suicide in Korean adolescents using machine learning techniques.

PloS one Jun 6, 2019
OBJECTIVE: Suicide in adolescents is a major problem worldwide and previous history of suicide ideation and attempt represents the strongest predictors of future suicidal behavior. The aim of this study was to develop prediction model to identify Kor...
Suicide ROC Curve Logistic Models Female Models, Theoretical Risk Factors Multivariate Analysis Humans Male Machine Learning Adolescent Republic of Korea
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Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques.

Clinical and translational science May 31, 2019
Applying data mining and machine learning (ML) techniques to clinical data might identify predictive biomarkers for diabetic nephropathy (DN), a common complication of type 2 diabetes mellitus (T2DM). A retrospective analysis of the Action to Control...
Risk Factors Models, Theoretical Sensitivity and Specificity Data Mining Male Humans Middle Aged Incidence Machine Learning ROC Curve Biomarkers Diabetes Mellitus, Type 2 Female Diabetic Nephropathies
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The Use of Deep Learning to Predict Stroke Patient Mortality.

International journal of environmental research and public health May 28, 2019
The increase in stroke incidence with the aging of the Korean population will rapidly impose an economic burden on society. Timely treatment can improve stroke prognosis. Awareness of stroke warning signs and appropriate actions in the event of a str...
Risk Factors Humans Deep Learning Neural Networks, Computer Stroke Prognosis Models, Biological
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Assessment of risk based on variant pathways and establishment of an artificial neural network model of thyroid cancer.

BMC medical genetics May 28, 2019
BACKGROUND: This study aimed to establish an artificial neural network (ANN) model based on variant pathways to predict the risk of thyroid cancer.
Humans Neural Networks, Computer Risk Factors Biomarkers, Tumor Signal Transduction Cluster Analysis Gene Expression Profiling Thyroid Neoplasms Gene Regulatory Networks Gene Expression Regulation, Neoplastic
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Estimating the association between antibiotic exposure and colonization with extended-spectrum β-lactamase-producing Gram-negative bacteria using machine learning methods: a multicentre, prospective cohort study.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases May 23, 2019
OBJECTIVES: The aim of the study was to measure the impact of antibiotic exposure on the acquisition of colonization with extended-spectrum β-lactamase-producing Gram-negative bacteria (ESBL-GNB) accounting for individual- and group-level confounding...
Adult Male Middle Aged Adolescent Incidence Italy beta-Lactamases Drug Therapy, Combination Risk Factors Hospitalization Aged Young Adult Anti-Bacterial Agents Prospective Studies Female Serbia Humans Gram-Negative Bacteria Machine Learning Gram-Negative Bacterial Infections Romania
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Automated detection of sudden unexpected death in epilepsy risk factors in electronic medical records using natural language processing.

Epilepsia May 21, 2019
OBJECTIVE: Sudden unexpected death in epilepsy (SUDEP) is an important cause of mortality in epilepsy. However, there is a gap in how often providers counsel patients about SUDEP. One potential solution is to electronically prompt clinicians to provi...
Epilepsy, Tonic-Clonic Sudden Unexpected Death in Epilepsy Sensitivity and Specificity Cross-Sectional Studies Algorithms Humans Natural Language Processing Retrospective Studies Epilepsy Data Interpretation, Statistical Electronic Health Records Neurosurgery Risk Factors Drug Resistant Epilepsy Death, Sudden
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A Precision Environment-Wide Association Study of Hypertension via Supervised Cadre Models.

IEEE journal of biomedical and health informatics May 20, 2019
We consider the problem in precision health of grouping people into subpopulations based on their degree of vulnerability to a risk factor. These subpopulations cannot be discovered with traditional clustering techniques because their quality is eval...
Big Data Computational Biology Nutrition Surveys Hypertension Humans Risk Factors Models, Statistical Supervised Machine Learning Environment Knowledge Discovery
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