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MIMIC |
Availability | Publicly available + |
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Blog | Survival Analysis of MIMIC-II ICU patients using Time-Sclicing Cox Regression Method + |
Cito:citesAsAuthority | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3124312/ + , http://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/1472-6947-13-9 + , https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4878278/ + |
Cito:citesAsDataSource | https://mimic.physionet.org/about/publications/ + , https://www.ncbi.nlm.nih.gov/pubmed/?term=("Medical+Information+Mart"[tiab]+AND+"Intensive+Care"[tiab])+OR+("Multiparameter+Intelligent+Monitoring"[tiab]+AND+"Intensive+Care"[tiab])+OR+-2 + |
Dcat:keyword | ICU patient + |
Dct:alternative | MIMIC + , Multiparameter Intelligent Monitoring in Intensive Care + |
Dct:description |
MIMIC is an openly available dataset devel … MIMIC is an openly available dataset developed by the MIT Lab for Computational Physiology, comprising deidentified health data associated with >40,000 critical care patients. It includes demographics, vital signs, laboratory tests, medications, and more. , laboratory tests, medications, and more. +
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Dct:license | http://www.gnu.org/licenses/gpl-2.0-standalone.html + |
Dct:publisher | https://www.physionet.org/ + |
Dct:references | https://mimic.physionet.org/about/mimic/ + |
Dct:rights |
MIMIC is made available largely through th … MIMIC is made available largely through the work of researchers at the MIT Laboratory for Computational Physiology and collaborating research groups. If you use our data, code or algorithms, please provide a citation to this project. Citation formats can be found on https://mimic.physionet.org/about/acknowledgments/. imic.physionet.org/about/acknowledgments/. +
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Dct:title | Medical Information Mart for Intensive Care + |
Foaf:page | https://mimic.physionet.org/ + |
Geographic area | Boston, MA + |
Idot:preferredPrefix | MIMIC + |
Methods in publications | ANOVA + , Bagging + , Boosting + , Bootstrap + , CART Algorithm + , CHAID + , Classification And Regression Tree + , Classification Based On Association + , Decision Stump + , EM Algorithm + , Genetic Algorithm + , Gini Index + , Information Gain + , Linear Discriminant Analysis + , Logistic Regression + , Naive Bayes + , Pearson Correlation Coefficient + , Perceptron + , Principal Component Analysis + , RIPPER + , Recurrent Neural Network + , Regression Model + , ReliefF + , SVAR Model + , Support Vector Machine + , Survival Analysis + , Wilcoxon + , Association Rule Mining + , Backward Stepwise Logistic Regression + , Ensemble Learning + , Gibbs Sampling Algorithm + , Kaplan-Meier Survival Analysis + , Kolmogorov-Smirnov + , Kruskal-Wallis + , Lasso Logistic Regression + , Linear Regression + , Majority Sense Baseline Classifier + , Mann-Whitney U Test + , McNemar's Test + , Multiscale Entropy + , Propensity Score Matching + , Reclassification Analysis + , Shapiro-Wilks Statistic + , Simple Linear Regression + , Stepwise Logistic Regression + , TREWScore + , Wald Test + , Cox Regression + , Feature Extraction Algorithm + , Backwardstepwise Logistic Regression + , Linear Regression Model + , K-nearest Neighbour + , Repeated Incremental Pruning To Produce Error Reduction + , Dimensionality Reduction Algorithm + , Expectation Maximization Algorithm + , Expectation Maximization + , K-nearest Neighbor + , Nearest Neighbor + , K-NN + , McNemars Test + , KolmogorovSmirnov + , T Test + , Analysis Of Variance + , Logistic Regression Model + , Chisquared + , Chi-square + , Mann-Whitney U-test + , Log-rank Test + , Kaplan-Meier Survival + , Propensity Score Analysis + , Ensemble Method + , Wilcoxon Rank Sum Test + , Chi-square Test + , K-means + , Feature Selection Method + , Cox Proportional Hazards + , TTEST + , KaplanMeier Survival + , Random Forests + , T-test + , MannWhitney + , Mann Whitney + , Fishers Exact Test + , Wilcoxon Rank-sum Test + , Chi-squared Test + , Levenes Test + , Long Rank Test + , Cox Proportional Hazards Survival Regression + , Chi Square Test + , Hazard Model + , Generative Model + , Ks Test + , Apriori + , Time Series Based + , Classification Model + , Instance-based Learning Algorithm + , Learn To Rank + , Learn-to-rank + , Paired Ttest + , Learning To Rank + , MannWhitney U Test + , Kaplan Meier Survival Curve + , Wilcoxon RankSum Test + , McNemar Test + , Fisher Exact Test + , Wilcoxon Signed Rank Test + , Deep Learning + , Bootstrap Aggregating + , Wrapper Feature Selection + , Filter Feature Selection + , Info Gain + , Cox Model + , Feature Extraction Method + , Proportional Hazards + , KNN + , Neural Network Model + , Information Gain Ratio + , Kmeans + , Poisson Regression + , Logrank Test + , Conditional Random Field + , Decision Tree Model + , Discriminative Model + , Missing Value Imputation Method + , Clustering Model + , VAR Model + , Targeted Real-time Early Warning Score + , KaplanMeier Survival Curve + , Multivariable Cox Proportional Hazards + , Kaplan-Meier Survival Curve + , T -test + , Mann-Whitney + , Chisquare Test + , Kruskal-Wallis Test + , Kruskal Wallis Test + , Chi-squared + , Modeling Algorithm + |
PPI | 30.4 + |
Patient type | ICU patients + |
Pav:hasCurrentVersion | MIMIC-III v1.4 + |
Publication number | 184 + |
Rdf:type | dctypes:Dataset + |
Schemaorg:logo | https://mimic.physionet.org/img/logo.png + |
Top methods in publications |
Logistic Regression (45.39%), Chi-Squared … Logistic Regression (45.39%), Chi-Squared Test (20.39%), T-Test (17.76%), Mann-Whitney U Test (15.79%), Regression Model (14.47%), Support Vector Machine (14.47%), Linear Regression (11.84%), Cox Regression (11.18%), Kolmogorov-Smirnov Test (9.87%), K-Nearest Neighbors (9.21%) Test (9.87%), K-Nearest Neighbors (9.21%) +
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Has query "Has query" is a predefined property that represents meta information (in form of a subobject) about individual queries.
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MIMIC + , MIMIC + |
Categories | Summary Level |
Modification date This property is a special property in this wiki.
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3 April 2018 14:13:55 + |
hide properties that link here |
MIMIC-II v2.6 + , MIMIC-III v1.3 + , MIMIC-III v1.4 + | Dct:isVersionOf |
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Survival Analysis of MIMIC-II ICU patients using Time-Sclicing Cox Regression Method + | For Dataset |