AIMC Topic: ROC Curve

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Early Detection of Heart Failure Using Electronic Health Records: Practical Implications for Time Before Diagnosis, Data Diversity, Data Quantity, and Data Density.

Circulation. Cardiovascular quality and outcomes Nov 8, 2016
BACKGROUND: Using electronic health records data to predict events and onset of diseases is increasingly common. Relatively little is known, although, about the tradeoffs between data requirements and model utility.
Early Diagnosis Pennsylvania Case-Control Studies Incidence Female Risk Factors Time Factors Male ROC Curve Humans Logistic Models Machine Learning Predictive Value of Tests Prognosis Area Under Curve Electronic Health Records Heart Failure Data Mining Risk Assessment
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A novel algorithm for ventricular arrhythmia classification using a fuzzy logic approach.

Australasian physical & engineering sciences in medicine Nov 4, 2016
In the present study, it has been shown that an unnecessary implantable cardioverter-defibrillator (ICD) shock is often delivered to patients with an ambiguous ECG rhythm in the overlap zone between ventricular tachycardia (VT) and ventricular fibril...
Humans Heart Ventricles Arrhythmias, Cardiac Databases as Topic Tachycardia, Ventricular Ventricular Fibrillation Algorithms ROC Curve Electrocardiography Fuzzy Logic
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RAFP-Pred: Robust Prediction of Antifreeze Proteins Using Localized Analysis of n-Peptide Compositions.

IEEE/ACM transactions on computational biology and bioinformatics Oct 13, 2016
In extreme cold weather, living organisms produce Antifreeze Proteins (AFPs) to counter the otherwise lethal intracellular formation of ice. Structures and sequences of various AFPs exhibit a high degree of heterogeneity, consequently the prediction ...
Dipeptides Sequence Analysis, Protein Antifreeze Proteins Algorithms ROC Curve Computational Biology Databases, Protein Machine Learning
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Individual prediction of long-term outcome in adolescents at ultra-high risk for psychosis: Applying machine learning techniques to brain imaging data.

Human brain mapping Oct 4, 2016
An important focus of studies of individuals at ultra-high risk (UHR) for psychosis has been to identify biomarkers to predict which individuals will transition to psychosis. However, the majority of individuals will prove to be resilient and go on t...
Magnetic Resonance Imaging Predictive Value of Tests Psychotic Disorders Neuropsychological Tests Adolescent Child ROC Curve Image Processing, Computer-Assisted Humans Machine Learning Brain Risk Factors Male Psychiatric Status Rating Scales
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Using administrative data to identify U.S. Army soldiers at high-risk of perpetrating minor violent crimes.

Journal of psychiatric research Sep 30, 2016
Growing concerns exist about violent crimes perpetrated by U.S. military personnel. Although interventions exist to reduce violent crimes in high-risk populations, optimal implementation requires evidence-based targeting. The goal of the current stud...
Risk Violence Incidence Humans Female Time Factors Young Adult Machine Learning Models, Theoretical ROC Curve Adult Socioeconomic Factors Databases, Factual United States Male Regression Analysis Adolescent Area Under Curve Military Personnel
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Sequence-Based Prediction of Protein-Carbohydrate Binding Sites Using Support Vector Machines.

Journal of chemical information and modeling Sep 22, 2016
Carbohydrate-binding proteins play significant roles in many diseases including cancer. Here, we established a machine-learning-based method (called sequence-based prediction of residue-level interaction sites of carbohydrates, SPRINT-CBH) to predict...
Humans Molecular Docking Simulation ROC Curve Protein Binding Carbohydrate Metabolism Support Vector Machine Proteins Databases, Protein Carbohydrates Binding Sites
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Machine learning approaches to personalize early prediction of asthma exacerbations.

Annals of the New York Academy of Sciences Sep 14, 2016
Patient telemonitoring results in an aggregation of significant amounts of information about patient disease trajectory. However, the potential use of this information for early prediction of exacerbations in adult asthma patients has not been system...
Telemedicine Bayes Theorem Internet Models, Biological Combined Modality Therapy Severity of Illness Index ROC Curve Decision Support Systems, Clinical Computational Biology Monitoring, Physiologic Humans Machine Learning Algorithms Precision Medicine Prognosis Electronic Health Records Adult Self Care Asthma Disease Progression
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Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

International journal of injury control and safety promotion Sep 8, 2016
Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too...
Humans Neural Networks, Computer Forecasting Female Adolescent ROC Curve Cluster Analysis Area Under Curve Accidents, Traffic Young Adult Adult Male Middle Aged United Arab Emirates Wounds and Injuries Trauma Severity Indices
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A mixed-ensemble model for hospital readmission.

Artificial intelligence in medicine Aug 31, 2016
OBJECTIVE: A hospital readmission is defined as an admission to a hospital within a certain time frame, typically thirty days, following a previous discharge, either to the same or to a different hospital. Because most patients are not readmitted, th...
Patient Readmission Hospitalization Humans Time Factors Forecasting ROC Curve Support Vector Machine Heart Failure
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Predicting lung cancer prognosis using machine learning.

The Lancet. Oncology Aug 25, 2016
Survival Analysis Image Interpretation, Computer-Assisted Automation Adenocarcinoma of Lung Carcinoma, Non-Small-Cell Lung Predictive Value of Tests Area Under Curve Neoplasm Staging Decision Support Techniques Carcinoma, Squamous Cell ROC Curve Lung Neoplasms Adenocarcinoma Humans Machine Learning Software
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