1
40
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Text
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URL Address
<a href="http://doi.org/10.1155/2013/873595" target="_blank" rel="noreferrer noopener">http://doi.org/10.1155/2013/873595</a>
Pages
873595–873595
Volume
2013
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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A gradient boosting algorithm for survival analysis via direct optimization of concordance index.
Publisher
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Computational and mathematical methods in medicine
Date
A point or period of time associated with an event in the lifecycle of the resource
2013
1905-07
Subject
The topic of the resource
*Survival Analysis; Algorithms; Artificial Intelligence; Breast Neoplasms/*epidemiology/*mortality; Clinical; Databases; Decision Support Systems; Factual; Female; Humans; Internet; Models; Prognosis; Proportional Hazards Models; Software; Theoretical
Creator
An entity primarily responsible for making the resource
Chen Yifei; Jia Zhenyu; Mercola Dan; Xie Xiaohui
Description
An account of the resource
Survival analysis focuses on modeling and predicting the time to an event of interest. Many statistical models have been proposed for survival analysis. They often impose strong assumptions on hazard functions, which describe how the risk of an event changes over time depending on covariates associated with each individual. In particular, the prevalent proportional hazards model assumes that covariates are multiplicatively related to the hazard. Here we propose a nonparametric model for survival analysis that does not explicitly assume particular forms of hazard functions. Our nonparametric model utilizes an ensemble of regression trees to determine how the hazard function varies according to the associated covariates. The ensemble model is trained using a gradient boosting method to optimize a smoothed approximation of the concordance index, which is one of the most widely used metrics in survival model performance evaluation. We implemented our model in a software package called GBMCI (gradient boosting machine for concordance index) and benchmarked the performance of our model against other popular survival models with a large-scale breast cancer prognosis dataset. Our experiment shows that GBMCI consistently outperforms other methods based on a number of covariate settings. GBMCI is implemented in R and is freely available online.
Identifier
An unambiguous reference to the resource within a given context
<a href="http://doi.org/10.1155/2013/873595" target="_blank" rel="noreferrer noopener">10.1155/2013/873595</a>
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Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
*Survival Analysis
2013
Algorithms
Artificial Intelligence
Breast Neoplasms/*epidemiology/*mortality
Chen Yifei
Clinical
Computational and mathematical methods in medicine
Databases
Decision Support Systems
Factual
Female
Humans
Internet
Jia Zhenyu
Mercola Dan
Models
Prognosis
Proportional Hazards Models
Software
Theoretical
Xie Xiaohui
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Text
A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.
URL Address
<a href="http://doi.org/10.1155/2014/316153" target="_blank" rel="noreferrer noopener">http://doi.org/10.1155/2014/316153</a>
Pages
316153–316153
Volume
2014
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Advances in statistical medicine.
Publisher
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Computational and mathematical methods in medicine
Date
A point or period of time associated with an event in the lifecycle of the resource
2014
1905-07
Subject
The topic of the resource
*Statistics as Topic; Biotechnology/trends; Computers; Decision Trees; Drug Design; Humans; Medical Informatics/*methods; Models; Neoplasms/therapy; Statistical
Creator
An entity primarily responsible for making the resource
Datta Sujay; Xia Xiao-Qin; Bhattacharjee Samsiddhi; Jia Zhenyu
Identifier
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<a href="http://doi.org/10.1155/2014/316153" target="_blank" rel="noreferrer noopener">10.1155/2014/316153</a>
Rights
Information about rights held in and over the resource
Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
*Statistics as Topic
2014
Bhattacharjee Samsiddhi
Biotechnology/trends
Computational and mathematical methods in medicine
Computers
Datta Sujay
Decision Trees
Drug Design
Humans
Jia Zhenyu
Medical Informatics/*methods
Models
Neoplasms/therapy
Statistical
Xia Xiao-Qin
-
Text
A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.
URL Address
<a href="http://doi.org/10.1155/2014/956917" target="_blank" rel="noreferrer noopener">http://doi.org/10.1155/2014/956917</a>
Pages
956917–956917
Volume
2014
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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A note regarding problems with interaction and varying block sizes in a comparison of endotracheal tubes.
Publisher
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Computational and mathematical methods in medicine
Date
A point or period of time associated with an event in the lifecycle of the resource
2014
1905-7
Subject
The topic of the resource
*Randomized Controlled Trials as Topic; *Research Design; Algorithms; Anesthesiology/*methods; Data Interpretation; Humans; Intratracheal/*instrumentation; Intubation; Models; Sample Size; Statistical; Treatment Outcome
Creator
An entity primarily responsible for making the resource
Einsporn Richard L; Jia Zhenyu
Description
An account of the resource
A randomized clinical experiment to compare two types of endotracheal tubes utilized a block design where each of the six participating anesthesiologists performed tube insertions for an equal number of patients for each type of tube. Five anesthesiologists intubated at least three patients with each tube type, but one anesthesiologist intubated only one patient per tube type. Overall, one type of tube outperformed the other on all three effectiveness measures. However, analysis of the data using an interaction model gave conflicting and misleading results, making the tube with the better performance appear to perform worse. This surprising result was caused by the undue influence of the data for the anesthesiologist who intubated only two patients. We therefore urge caution in interpreting results from interaction models with designs containing small blocks.
Identifier
An unambiguous reference to the resource within a given context
<a href="http://doi.org/10.1155/2014/956917" target="_blank" rel="noreferrer noopener">10.1155/2014/956917</a>
Rights
Information about rights held in and over the resource
Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
*Randomized Controlled Trials as Topic
*Research Design
2014
Algorithms
Anesthesiology/*methods
Computational and mathematical methods in medicine
Data Interpretation
Einsporn Richard L
Humans
Intratracheal/*instrumentation
Intubation
Jia Zhenyu
Models
Sample Size
Statistical
Treatment Outcome
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Text
A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.
URL Address
<a href="http://doi.org/10.1155/2014/643457" target="_blank" rel="noreferrer noopener">http://doi.org/10.1155/2014/643457</a>
Pages
643457–643457
Volume
2014
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
A name given to the resource
Weighted Lin-Wang tests for crossing hazards.
Publisher
An entity responsible for making the resource available
Computational and mathematical methods in medicine
Date
A point or period of time associated with an event in the lifecycle of the resource
2014
1905-07
Subject
The topic of the resource
*Survival Analysis; Algorithms; Animal; Animals; Computer Simulation; Data Interpretation; Disease Models; Humans; Kaplan-Meier Estimate; Leukemia/drug therapy; Mice; Models; Reproducibility of Results; Statistical
Creator
An entity primarily responsible for making the resource
Koziol James A; Jia Zhenyu
Description
An account of the resource
Lin and Wang have introduced a quadratic version of the logrank test, appropriate for situations in which the underlying survival distributions may cross. In this note, we generalize the Lin-Wang procedure to incorporate weights and investigate the performance of Lin and Wang's test and weighted versions in various scenarios. We find that weighting does increase statistical power in certain situations; however, none of the procedures was dominant under every scenario.
Identifier
An unambiguous reference to the resource within a given context
<a href="http://doi.org/10.1155/2014/643457" target="_blank" rel="noreferrer noopener">10.1155/2014/643457</a>
Rights
Information about rights held in and over the resource
Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
*Survival Analysis
2014
Algorithms
Animal
Animals
Computational and mathematical methods in medicine
Computer Simulation
Data Interpretation
Disease Models
Humans
Jia Zhenyu
Kaplan-Meier Estimate
Koziol James A
Leukemia/drug therapy
Mice
Models
Reproducibility of Results
Statistical
-
Text
A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.
URL Address
<a href="http://doi.org/10.1155/2014/746979" target="_blank" rel="noreferrer noopener">http://doi.org/10.1155/2014/746979</a>
Pages
746979–746979
Volume
2014
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Establishing reliable miRNA-cancer association network based on text-mining method.
Publisher
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Computational and mathematical methods in medicine
Date
A point or period of time associated with an event in the lifecycle of the resource
2014
1905-7
Subject
The topic of the resource
Algorithms; Area Under Curve; Computational Biology/*methods; Data Mining/*methods; False Positive Reactions; Gene Expression Profiling/methods; Gene Expression Regulation; Gene Regulatory Networks; Humans; MicroRNAs/*genetics/*metabolism; Neoplasms/*genetics/metabolism; Neoplastic; Probability; Reproducibility of Results
Creator
An entity primarily responsible for making the resource
Li Lun; Hu Xingchi; Yang Zhaowan; Jia Zhenyu; Fang Ming; Zhang Libin; Zhou Yanhong
Description
An account of the resource
Associating microRNAs (miRNAs) with cancers is an important step of understanding the mechanisms of cancer pathogenesis and finding novel biomarkers for cancer therapies. In this study, we constructed a miRNA-cancer association network (miCancerna) based on more than 1,000 miRNA-cancer associations detected from millions of abstracts with the text-mining method, including 226 miRNA families and 20 common cancers. We further prioritized cancer-related miRNAs at the network level with the random-walk algorithm, achieving a relatively higher performance than previous miRNA disease networks. Finally, we examined the top 5 candidate miRNAs for each kind of cancer and found that 71% of them are confirmed experimentally. miCancerna would be an alternative resource for the cancer-related miRNA identification.
Identifier
An unambiguous reference to the resource within a given context
<a href="http://doi.org/10.1155/2014/746979" target="_blank" rel="noreferrer noopener">10.1155/2014/746979</a>
Rights
Information about rights held in and over the resource
Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
2014
Algorithms
Area Under Curve
Computational and mathematical methods in medicine
Computational Biology/*methods
Data Mining/*methods
False Positive Reactions
Fang Ming
Gene Expression Profiling/methods
Gene Expression Regulation
Gene Regulatory Networks
Hu Xingchi
Humans
Jia Zhenyu
Li Lun
MicroRNAs/*genetics/*metabolism
Neoplasms/*genetics/metabolism
Neoplastic
Probability
Reproducibility of Results
Yang Zhaowan
Zhang Libin
Zhou Yanhong