AIMC Topic: ROC Curve

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Machine learning-based classification of diffuse large B-cell lymphoma patients by eight gene expression profiles.

Cancer medicine Feb 11, 2016
Gene expression profiling (GEP) had divided the diffuse large B-cell lymphoma (DLBCL) into molecular subgroups: germinal center B-cell like (GCB), activated B-cell like (ABC), and unclassified (UC) subtype. However, this classification with prognosti...
Antineoplastic Combined Chemotherapy Protocols Treatment Outcome Support Vector Machine Databases, Genetic Male Middle Aged Gene Expression Profiling ROC Curve Rituximab Vincristine Genes, Neoplasm Antibodies, Monoclonal, Murine-Derived Germinal Center Doxorubicin Survival Analysis Cyclophosphamide Prednisone Humans Aged Sensitivity and Specificity Lymphoma, Large B-Cell, Diffuse Prognosis Female
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Combining Amplitude Spectrum Area with Previous Shock Information Using Neural Networks Improves Prediction Performance of Defibrillation Outcome for Subsequent Shocks in Out-Of-Hospital Cardiac Arrest Patients.

PloS one Feb 10, 2016
OBJECTIVE: Quantitative ventricular fibrillation (VF) waveform analysis is a potentially powerful tool to optimize defibrillation. However, whether combining VF features with additional attributes that related to the previous shock could enhance the ...
Defibrillators Out-of-Hospital Cardiac Arrest Humans Neural Networks, Computer Software Retrospective Studies Signal Processing, Computer-Assisted Predictive Value of Tests Sensitivity and Specificity Electric Countershock Area Under Curve ROC Curve Ventricular Fibrillation Electrocardiography Treatment Outcome
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A Systematic Strategy for Screening and Application of Specific Biomarkers in Hepatotoxicity Using Metabolomics Combined With ROC Curves and SVMs.

Toxicological sciences : an official journal of the Society of Toxicology Jan 18, 2016
Current studies that evaluate toxicity based on metabolomics have primarily focused on the screening of biomarkers while largely neglecting further verification and biomarker applications. For this reason, we used drug-induced hepatotoxicity as an ex...
Support Vector Machine Metabolomics Liver Chromatography, High Pressure Liquid Atorvastatin Chemical and Drug Induced Liver Injury Carbon Tetrachloride Acetaminophen Animals Male ROC Curve Rats, Wistar Biomarkers Sensitivity and Specificity
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Benchmarking Deep Networks for Predicting Residue-Specific Quality of Individual Protein Models in CASP11.

Scientific reports Jan 14, 2016
Quality assessment of a protein model is to predict the absolute or relative quality of a protein model using computational methods before the native structure is available. Single-model methods only need one model as input and can predict the absolu...
Models, Molecular Amino Acids Protein Conformation Algorithms ROC Curve Support Vector Machine Proteins
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A novel mathematical model to predict prognosis of burnt patients based on logistic regression and support vector machine.

Burns : journal of the International Society for Burn Injuries Jan 13, 2016
OBJECTIVE: To develop a mathematical model of predicting mortality based on the admission characteristics of 6220 burn cases.
Adult Middle Aged Infant Adolescent Prognosis Infant, Newborn Aged Young Adult Models, Theoretical Support Vector Machine Principal Component Analysis Burns Shock Child, Preschool Child ROC Curve Logistic Models Humans Multivariate Analysis Body Surface Area Smoke Inhalation Injury Trauma Severity Indices
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Brain-inspired cheminformatics of drug-target brain interactome, synthesis, and assay of TVP1022 derivatives.

Neuropharmacology Dec 23, 2015
The use of Cheminformatics tools is gaining importance in the field of translational research from Medicinal Chemistry to Neuropharmacology. In particular, we need it for the analysis of chemical information on large datasets of bioactive compounds. ...
ROC Curve Computational Biology Humans Neuroprotective Agents Algorithms Indans Neural Networks, Computer Brain Drug Delivery Systems Animals
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Reverse Engineering and Evaluation of Prediction Models for Progression to Type 2 Diabetes: An Application of Machine Learning Using Electronic Health Records.

Journal of diabetes science and technology Dec 20, 2015
BACKGROUND: Application of novel machine learning approaches to electronic health record (EHR) data could provide valuable insights into disease processes. We utilized this approach to build predictive models for progression to prediabetes and type 2...
ROC Curve Diabetes Mellitus, Type 2 Area Under Curve Medical Informatics Prediabetic State Risk Factors Adult Male Humans Disease Progression Machine Learning Retrospective Studies Electronic Health Records Female
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GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran.

Environmental monitoring and assessment Dec 19, 2015
Groundwater is considered one of the most valuable fresh water resources. The main objective of this study was to produce groundwater spring potential maps in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran, using three machine learnin...
Machine Learning Geographic Information Systems ROC Curve Models, Theoretical Groundwater Iran Environmental Monitoring Water Resources Rivers Models, Statistical Geology Decision Trees
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Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes.

BMC bioinformatics Dec 9, 2015
BACKGROUND: Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been develo...
Protein Structure, Tertiary Dimerization Proteins ROC Curve Protein Interaction Maps Principal Component Analysis Protein Binding Area Under Curve Support Vector Machine Hydrogen Bonding
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Machine learning to assist risk-of-bias assessments in systematic reviews.

International journal of epidemiology Dec 8, 2015
BACKGROUND: Risk-of-bias assessments are now a standard component of systematic reviews. At present, reviewers need to manually identify relevant parts of research articles for a set of methodological elements that affect the risk of bias, in order t...
Machine Learning ROC Curve Logistic Models Humans Bias Review Literature as Topic Data Mining Datasets as Topic
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