Constantin F. Aliferis - researchr alias

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Viewing Publication 1 - 61 from 61

2018

2015

Computational Methods for Unraveling Temporal Brain Connectivity DataBisakha Ray, Constantin F. Aliferis, Alexander R. Statnikov. amia 2015: [doi]

Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discoveryAlexander R. Statnikov, Sisi Ma, Mikael Henaff, Nikita I. Lytkin, Efstratios Efstathiadis, Eric R. Peskin, Constantin F. Aliferis. jmlr, 16:3219-3267, 2015. [doi]

2014

2013

2011

A comparison of evaluation metrics for biomedical journals, articles, and websites in terms of sensitivity to topicLawrence D. Fu, Yindalon Aphinyanaphongs, Lily Wang, Constantin F. Aliferis. jbi, 44(4):587-594, 2011. [doi]

Time Series Analysis with the Causality WorkbenchIsabelle Guyon, Alexander Satnikov, Constantin F. Aliferis. jmlr, 12:115-139, 2011. [doi]

2010

Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and ExtensionsConstantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos. jmlr, 11:235-284, 2010. [doi]

Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical EvaluationConstantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos. jmlr, 11:171-234, 2010. [doi]

Using content-based and bibliometric features for machine learning models to predict citation counts in the biomedical literatureLawrence D. Fu, Constantin F. Aliferis. scientometrics, 85(1):257-270, 2010. [doi]

Bayesian Algorithms for Causal Data MiningSubramani Mani, Constantin F. Aliferis, Alexander R. Statnikov. jmlr, 6:121-136, 2010. [doi]

TIED: An Artificially Simulated Dataset with Multiple Markov BoundariesAlexander R. Statnikov, Constantin F. Aliferis. jmlr, 6:249-256, 2010. [doi]

Analysis and Computational Dissection of Molecular Signature MultiplicityAlexander R. Statnikov, Constantin F. Aliferis. ploscb, 6(5), 2010. [doi]

2009

The FAST-AIMS Clinical Mass Spectrometry Analysis SystemNafeh Fananapazir, Alexander R. Statnikov, Constantin F. Aliferis. abi, 2009, 2009. [doi]

2008

2007

Text Categorization Models for Identifying Unproven Cancer Treatments on the WebYin Aphinyanaphongs, Constantin F. Aliferis. medinfo 2007: 968-972 [doi]

A Comparison of Impact Factor, Clinical Query Filters, and Pattern Recognition Query Filters in Terms of Sensitivity to TopicLawrence D. Fu, Lily Wang, Yindalon Aphinyanagphongs, Constantin F. Aliferis. medinfo 2007: 716-720 [doi]

A Causal Modeling Framework for Generating Clinical Practice Guidelines from DataSubramani Mani, Constantin F. Aliferis. aime 2007: 446-450 [doi]

Learning Causal and Predictive Clinical Practice Guidelines from DataSubramani Mani, Constantin F. Aliferis, Shanthi Krishnaswami, Theodore Kotchen. medinfo 2007: 850-854 [doi]

Are Random Forests Better than Support Vector Machines for Microarray-Based Cancer Classification?Alexander R. Statnikov, Constantin F. Aliferis. amia 2007: [doi]

2006

Prospective Validation of Text Categorization Filters for Identifying High-Quality, Content-Specific Articles in MEDLINEYindalon Aphinyanaphongs, Constantin F. Aliferis. amia 2006: [doi]

Research Paper: A Comparison of Citation Metrics to Machine Learning Filters for the Identification of High Quality MEDLINE DocumentsYindalon Aphinyanaphongs, Alexander R. Statnikov, Constantin F. Aliferis. jamia, 13(4):446-455, 2006. [doi]

Research Paper: Using Citation Data to Improve Retrieval from MEDLINEElmer V. Bernstam, Jorge R. Herskovic, Yindalon Aphinyanaphongs, Constantin F. Aliferis, Madurai G. Sriram, William R. Hersh. jamia, 13(1):96-105, 2006. [doi]

The max-min hill-climbing Bayesian network structure learning algorithmIoannis Tsamardinos, Laura E. Brown, Constantin F. Aliferis. ml, 65(1):31-78, 2006. [doi]

Generating Realistic Large Bayesian Networks by TilingIoannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown, Constantin F. Aliferis. flairs 2006: 592-597

2005

Research Paper: Text Categorization Models for High-Quality Article Retrieval in Internal MedicineYindalon Aphinyanaphongs, Ioannis Tsamardinos, Alexander R. Statnikov, Douglas Hardin, Constantin F. Aliferis. jamia, 12(2):207-216, 2005. [doi]

A Comparison of Novel and State-of-the-Art Polynomial Bayesian Network Learning AlgorithmsLaura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis. AAAI 2005: 739-745

Predicting dire outcomes of patients with community acquired pneumoniaGregory F. Cooper, Vijoy Abraham, Constantin F. Aliferis, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Janine E. Janosky, Gary Livingston, Tom M. Mitchell. jbi, 38(5):347-366, 2005. [doi]

Extracting Drug-Drug Interaction Articles from MEDLINE to Improve the Content of Drug DatabasesStephany Duda, Constantin F. Aliferis, Randolph A. Miller, Alexander R. Statnikov, Kevin B. Johnson. amia 2005: [doi]

Formative Evaluation of a Prototype System for Automated Analysis of Mass Spectrometry DataNafeh Fananapazir, M. Li, D. Spentzos, Constantin F. Aliferis. amia 2005: [doi]

Modeling Clinical Judgment and Implicit Guideline Compliance in the Diagnosisof Melanomas Using Machine LearningAndrea Sboner, Constantin F. Aliferis. amia 2005: [doi]

A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosisAlexander R. Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos, Douglas Hardin, Shawn Levy. bioinformatics, 21(5):631-643, 2005. [doi]

GEMS: A system for automated cancer diagnosis and biomarker discovery from microarray gene expression dataAlexander R. Statnikov, Ioannis Tsamardinos, Yerbolat Dosbayev, Constantin F. Aliferis. ijmi, 74(7-8):491-503, 2005. [doi]

Using the GEMS System for Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression DataAlexander R. Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis. AAAI 2005: 1710-1711

GEMS System for Supervised Analysis of Cancer Microarray Gene Expression DataAlexander R. Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis. amia 2005: [doi]

2004

2003

Machine Learning Models for Classification of Lung Cancer and Selection of Genomic Markers Using Array Gene Expression DataConstantin F. Aliferis, Ioannis Tsamardinos, P. Massion, Alexander R. Statnikov, N. Fananapazir, Douglas Hardin. flairs 2003: 67-71

Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical DiscoveryConstantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown. metmbs 2003: 371-376

HITON: A Novel Markov Blanket Algorithm for Optimal Variable SelectionConstantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov. amia 2003: [doi]

Why Classification Models Using Array Gene Expression Data Perform So Well: A Preliminary Investigation of Explanatory FactorsConstantin F. Aliferis, Ioannis Tsamardinos, P. Massion, Alexander R. Statnikov, Douglas Hardin. metmbs 2003: 47-53

Text Categorization Models for Retrieval of High Quality Articles in Internal MedicineYindalon Aphinyanaphongs, Constantin F. Aliferis. amia 2003: [doi]

Identifying Markov Blankets with Decision Tree InductionLewis Frey, Douglas H. Fisher, Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov. icdm 2003: 59-66 [doi]

Towards Principled Feature Selection: Relevancy, Filters and WrappersIoannis Tsamardinos, Constantin F. Aliferis. aistats 2003: [doi]

Algorithms for Large Scale Markov Blanket DiscoveryIoannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov. flairs 2003: 376-381

Time and sample efficient discovery of Markov blankets and direct causal relationsIoannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov. kdd 2003: 673-678 [doi]

2002

Machine learning models for lung cancer classification using array comparative genomic hybridizationConstantin F. Aliferis, Douglas P. Hardin, Pierre P. Massion. amia 2002: [doi]

1998

Temporal representation design principles: an assessment in the domain of liver transplantationConstantin F. Aliferis, Gregory F. Cooper. amia 1998: [doi]

1997

1996

A Structurally and Temporally Extended Bayesian Belief Network Model: Definitions, Properties, and Modeling TechniquesConstantin F. Aliferis, Gregory F. Cooper. uai 1996: 28-39 [doi]

Research Paper: A Temporal Analysis of QMRConstantin F. Aliferis, Gregory F. Cooper, Randolph A. Miller, Bruce G. Buchanan, Richard Bankowitz, Nunzia Bettinsoli Giuse. jamia, 3(1):79-91, 1996. [doi]

1994

An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Using Simulated Data SetsConstantin F. Aliferis, Gregory F. Cooper. uai 1994: 8-14 [doi]

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