AIMC Topic: Risk Assessment

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Comparison of Machine Learning Methods With National Cardiovascular Data Registry Models for Prediction of Risk of Bleeding After Percutaneous Coronary Intervention.

JAMA network open Jul 3, 2019
IMPORTANCE: Better prediction of major bleeding after percutaneous coronary intervention (PCI) may improve clinical decisions aimed to reduce bleeding risk. Machine learning techniques, bolstered by better selection of variables, hold promise for enh...
Humans Coronary Artery Disease Machine Learning Risk Adjustment Female Comparative Effectiveness Research Aged Male Clinical Decision Rules Postoperative Hemorrhage Registries Percutaneous Coronary Intervention Risk Assessment United States Models, Statistical
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Machine Learning Approach to Inpatient Violence Risk Assessment Using Routinely Collected Clinical Notes in Electronic Health Records.

JAMA network open Jul 3, 2019
IMPORTANCE: Inpatient violence remains a significant problem despite existing risk assessment methods. The lack of robustness and the high degree of effort needed to use current methods might be mitigated by using routinely registered clinical notes.
Machine Learning Prognosis Electronic Health Records Female Reproducibility of Results Humans Inpatients Risk Factors Netherlands Behavior Observation Techniques Violence Adult Hospitals, Psychiatric Male Aggression Middle Aged Risk Assessment
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Transfusion after total knee arthroplasty can be predicted using the machine learning algorithm.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Jun 28, 2019
PURPOSE: A blood transfusion after total knee arthroplasty (TKA) is associated with an increase in complication and infection rates. However, no studies have been conducted to predict transfusion after TKA using a machine learning algorithm. The purp...
Humans Machine Learning Algorithms Retrospective Studies Female Arthroplasty, Replacement, Knee Platelet Count ROC Curve Aged Blood Transfusion Adult Area Under Curve Male Hemoglobins Middle Aged Tranexamic Acid Risk Assessment
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Respiratory Sound Based Classification of Chronic Obstructive Pulmonary Disease: a Risk Stratification Approach in Machine Learning Paradigm.

Journal of medical systems Jun 28, 2019
This article investigates the classification of normal and COPD subjects on the basis of respiratory sound analysis using machine learning techniques. Thirty COPD and 25 healthy subject data are recorded. Total of 39 lung sound features and 3 spirome...
Support Vector Machine Forced Expiratory Volume Spirometry Vital Capacity Respiratory Sounds Female Humans Pulmonary Disease, Chronic Obstructive Machine Learning Sensitivity and Specificity Male Algorithms Risk Assessment Logistic Models
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A Machine Learning-Based Approach for the Prediction of Acute Coronary Syndrome Requiring Revascularization.

Journal of medical systems Jun 28, 2019
The aim of this study is to predict acute coronary syndrome (ACS) requiring revascularization in those patients presenting early-stage angina-like symptom using machine learning algorithms. We obtained data from 2344 ACS patients, who required revasc...
Risk Assessment ROC Curve Predictive Value of Tests Acute Coronary Syndrome Myocardial Revascularization Humans Machine Learning Algorithms Female Male
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Imaging Quality Control in the Era of Artificial Intelligence.

Journal of the American College of Radiology : JACR Jun 26, 2019
The advent of artificial intelligence (AI) promises to have a transformational impact on quality in medicine, including in radiology. However, experience has shown that quality tools alone are often not sufficient to bring about consistent excellent ...
Risk Assessment Diagnostic Imaging Automation Humans Radiology Radiation Exposure Artificial Intelligence Positron-Emission Tomography Forecasting Quality Control Tomography, X-Ray Computed
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Leveraging Machine Learning Techniques to Forecast Patient Prognosis After Percutaneous Coronary Intervention.

JACC. Cardiovascular interventions Jun 26, 2019
OBJECTIVES: This study sought to determine whether machine learning can be used to better identify patients at risk for death or congestive heart failure (CHF) rehospitalization after percutaneous coronary intervention (PCI).
Minnesota Risk Assessment Time Factors Hospital Mortality Treatment Outcome Predictive Value of Tests Reproducibility of Results Humans Registries Risk Factors Machine Learning Percutaneous Coronary Intervention Aged Decision Support Techniques Coronary Artery Disease Male Clinical Decision-Making Heart Failure Middle Aged Female Patient Readmission
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A machine learning approach for predictive models of adverse events following spine surgery.

The spine journal : official journal of the North American Spine Society Jun 20, 2019
BACKGROUND: Rates of adverse events following spine surgery vary widely by patient-, diagnosis-, and procedure-related factors. It is critical to understand the expected rates of complications and to be able to implement targeted efforts at limiting ...
Spine Odds Ratio Orthopedic Procedures Postoperative Complications Comorbidity Logistic Models United States Area Under Curve Humans Machine Learning Databases, Factual Male Retrospective Studies Middle Aged Female Risk Assessment Aged
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Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines.

Circulation. Arrhythmia and electrophysiology Jun 20, 2019
BACKGROUND: Cardiac resynchronization therapy (CRT) has significant nonresponse rates. We assessed whether machine learning (ML) could predict CRT response beyond current guidelines.
Machine Learning Decision Support Techniques Retrospective Studies Clinical Decision-Making Female Humans Echocardiography Middle Aged Risk Assessment Disease Progression Time Factors Recovery of Function Risk Factors Aged Male Ventricular Function, Left Stroke Volume Practice Guidelines as Topic Heart-Assist Devices Heart Transplantation Ohio Baltimore Predictive Value of Tests Patient Selection Heart Failure Cardiac Resynchronization Therapy Progression-Free Survival
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Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models.

Breast cancer research : BCR Jun 20, 2019
BACKGROUND: Comprehensive breast cancer risk prediction models enable identifying and targeting women at high-risk, while reducing interventions in those at low-risk. Breast cancer risk prediction models used in clinical practice have low discriminat...
Genetic Predisposition to Disease Models, Theoretical Population Surveillance Disease Susceptibility Algorithms Precision Medicine Prognosis Female Adult Breast Neoplasms Middle Aged Risk Assessment Big Data ROC Curve Humans Machine Learning
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