Constantin F. Aliferis

Publication Activity (10 Years)

Years Active: 1994-2018
Publications (10 Years): 1

Top Topics

Medical Decision Support

Feature Selection

Bayesian Belief Networks

Top Venues

J. Mach. Learn. Res.

Publications

Boris Winterhoff, Stefan Kommoss, Florian Heitz, Gottfried Konecny, Sean Dowdy, Sally Mullany, Tjoung-won Simon, Klaus Baumann, Felix Hilpert, Sara Brucker, Andreas du Bios, Willibald Schröde, Alexander Burges, Steven Shen, Jinhua Wang, Roshan Tourani, Sisi Ma, Jacobus Pfisterer, Constantin F. Aliferis
Developing a Clinico-Molecular Test for Individualized Treatment of Ovarian Cancer: The interplay of Precision Medicine Informatics with Clinical and Health Economics Dimensions. AMIA (2018)
Bisakha Ray, Constantin F. Aliferis, Alexander R. Statnikov
Computational Methods for Unraveling Temporal Brain Connectivity Data. AMIA (2015)
Alexander R. Statnikov, Sisi Ma, Mikael Henaff, Nikita I. Lytkin, Efstratios Efstathiadis, Eric R. Peskin, Constantin F. Aliferis
Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discovery. J. Mach. Learn. Res. 16 (2015)
Subramani Mani, Asli Ozdas, Constantin F. Aliferis, Huseyin Atakan Varol, Qingxia Chen, Randy J. Carnevale, Yukun Chen, Joann Romano-Keeler, Hui Nian, Jörn-Hendrik Weitkamp
Medical decision support using machine learning for early detection of late-onset neonatal sepsis. J. Am. Medical Informatics Assoc. 21 (2) (2014)
Yindalon Aphinyanaphongs, Lawrence D. Fu, Zhiguo Li, Eric R. Peskin, Efstratios Efstathiadis, Constantin F. Aliferis, Alexander R. Statnikov
A comprehensive empirical comparison of modern supervised classification and feature selection methods for text categorization. J. Assoc. Inf. Sci. Technol. 65 (10) (2014)
Constantin F. Aliferis, Gregory F. Cooper
A Structurally and Temporally Extended Bayesian Belief Network Model: Definitions, Properties, and Modeling Techniques CoRR (2013)
Yindalon Aphinyanaphongs, Lawrence D. Fu, Constantin F. Aliferis
Identifying Unproven Cancer Treatments on the Health Web: Addressing Accuracy, Generalizability and Scalability. MedInfo (2013)
Lawrence D. Fu, Yindalon Aphinyanaphongs, Constantin F. Aliferis
Computer models for identifying instrumental citations in the biomedical literature. Scientometrics 97 (3) (2013)
Alexander R. Statnikov, Jan Lemeire, Constantin F. Aliferis
Algorithms for discovery of multiple Markov boundaries. J. Mach. Learn. Res. 14 (1) (2013)
Constantin F. Aliferis, Gregory F. Cooper
An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Usin CoRR (2013)
Titus Schleyer, Blackford Middleton, Bret Shillingstad, J. Marc Overhage, Constantin F. Aliferis
Informaticians, CxIOs and Industry: Strengthening the Fabric of HealthIT. AMIA (2013)
Lawrence D. Fu, Yindalon Aphinyanaphongs, Lily Wang, Constantin F. Aliferis
A comparison of evaluation metrics for biomedical journals, articles, and websites in terms of sensitivity to topic. J. Biomed. Informatics 44 (4) (2011)
Isabelle Guyon, Alexander R. Statnikov, Constantin F. Aliferis
Time Series Analysis with the Causality Workbench. NIPS Mini-Symposium on Causality in Time Series (2011)
Alexander R. Statnikov, Constantin F. Aliferis
Analysis and Computational Dissection of Molecular Signature Multiplicity. PLoS Comput. Biol. 6 (5) (2010)
Alexander R. Statnikov, Constantin F. Aliferis
TIED: An Artificially Simulated Dataset with Multiple Markov Boundaries. NIPS Causality: Objectives and Assessment (2010)
Subramani Mani, Constantin F. Aliferis, Alexander R. Statnikov
Bayesian Algorithms for Causal Data Mining. NIPS Causality: Objectives and Assessment (2010)
Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions. J. Mach. Learn. Res. 11 (2010)
Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation. J. Mach. Learn. Res. 11 (2010)
Lawrence D. Fu, Constantin F. Aliferis
Using content-based and bibliometric features for machine learning models to predict citation counts in the biomedical literature. Scientometrics 85 (1) (2010)
Nafeh Fananapazir, Alexander R. Statnikov, Constantin F. Aliferis
The FAST-AIMS Clinical Mass Spectrometry Analysis System. Adv. Bioinformatics 2009 (2009)
Alexander R. Statnikov, Lily Wang, Constantin F. Aliferis
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification. BMC Bioinform. 9 (2008)
Isabelle Guyon, Constantin F. Aliferis, Gregory F. Cooper, André Elisseeff, Jean-Philippe Pellet, Peter Spirtes, Alexander R. Statnikov
Design and Analysis of the Causation and Prediction Challenge. WCCI Causation and Prediction Challenge (2008)
Lawrence D. Fu, Constantin F. Aliferis
Models for Predicting and Explaining Citation Count of Biomedical Articles. AMIA (2008)
Subramani Mani, Constantin F. Aliferis
A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data. AIME (2007)
Lawrence D. Fu, Lily Wang, Yindalon Aphinyanagphongs, Constantin F. Aliferis
A Comparison of Impact Factor, Clinical Query Filters, and Pattern Recognition Query Filters in Terms of Sensitivity to Topic. MedInfo (2007)
Subramani Mani, Constantin F. Aliferis, Shanthi Krishnaswami, Theodore Kotchen
Learning Causal and Predictive Clinical Practice Guidelines from Data. MedInfo (2007)
Yindalon Aphinyanaphongs, Constantin F. Aliferis
Text Categorization Models for Identifying Unproven Cancer Treatments on the Web. MedInfo (2007)
Alexander R. Statnikov, Constantin F. Aliferis
Are Random Forests Better than Support Vector Machines for Microarray-Based Cancer Classification? AMIA (2007)
Ioannis Tsamardinos, Laura E. Brown, Constantin F. Aliferis
The max-min hill-climbing Bayesian network structure learning algorithm. Mach. Learn. 65 (1) (2006)
Elmer V. Bernstam, Jorge R. Herskovic, Yindalon Aphinyanaphongs, Constantin F. Aliferis, Madurai G. Sriram, William R. Hersh
Research Paper: Using Citation Data to Improve Retrieval from MEDLINE. J. Am. Medical Informatics Assoc. 13 (1) (2006)
Yindalon Aphinyanaphongs, Alexander R. Statnikov, Constantin F. Aliferis
Research Paper: A Comparison of Citation Metrics to Machine Learning Filters for the Identification of High Quality MEDLINE Documents. J. Am. Medical Informatics Assoc. 13 (4) (2006)
Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown, Constantin F. Aliferis
Generating Realistic Large Bayesian Networks by Tiling. FLAIRS Conference (2006)
Yindalon Aphinyanaphongs, Constantin F. Aliferis
Prospective Validation of Text Categorization Filters for Identifying High-Quality, Content-Specific Articles in MEDLINE. AMIA (2006)
Yindalon Aphinyanaphongs, Ioannis Tsamardinos, Alexander R. Statnikov, Douglas P. Hardin, Constantin F. Aliferis
Research Paper: Text Categorization Models for High-Quality Article Retrieval in Internal Medicine. J. Am. Medical Informatics Assoc. 12 (2) (2005)
Andrea Sboner, Constantin F. Aliferis
Modeling Clinical Judgment and Implicit Guideline Compliance in the Diagnosisof Melanomas Using Machine Learning. AMIA (2005)
Alexander R. Statnikov, Ioannis Tsamardinos, Yerbolat Dosbayev, Constantin F. Aliferis
GEMS: A system for automated cancer diagnosis and biomarker discovery from microarray gene expression data. Int. J. Medical Informatics 74 (7-8) (2005)
Alexander R. Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos, Douglas P. Hardin, Shawn Levy
A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis. Bioinform. 21 (5) (2005)
Gregory 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
Predicting dire outcomes of patients with community acquired pneumonia. J. Biomed. Informatics 38 (5) (2005)
Alexander R. Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis
Using the GEMS System for Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data. AAAI (2005)
Alexander R. Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis
System for Supervised Analysis of Cancer Microarray Gene Expression Data. AMIA (2005)
Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis
A Comparison of Novel and State-of-the-Art Polynomial Bayesian Network Learning Algorithms. AAAI (2005)
Nafeh Fananapazir, M. Li, D. Spentzos, Constantin F. Aliferis
Formative Evaluation of a Prototype System for Automated Analysis of Mass Spectrometry Data. AMIA (2005)
Stephany Duda, Constantin F. Aliferis, Randolph A. Miller, Alexander R. Statnikov, Kevin B. Johnson
Extracting Drug-Drug Interaction Articles from MEDLINE to Improve the Content of Drug Databases. AMIA (2005)
Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis
A Novel Algorithm for Scalable and Accurate Bayesian Network Learning. MedInfo (2004)
Douglas P. Hardin, Ioannis Tsamardinos, Constantin F. Aliferis
A theoretical characterization of linear SVM-based feature selection. ICML (2004)
Yin Aphinyanaphongs, Constantin F. Aliferis
Learning Boolean Queries for Article Quality Filtering. MedInfo (2004)
Alexander R. Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos
Methods for Multi-Category Cancer Diagnosis from Gene Expression Data: A Comprehensive Evaluation to Inform Decision Support System Development. MedInfo (2004)
Constantin F. Aliferis, Ioannis Tsamardinos, Pierre P. Massion, Alexander R. Statnikov, Nafeh Fananapazir, Douglas P. Hardin
Machine Learning Models for Classification of Lung Cancer and Selection of Genomic Markers Using Array Gene Expression Data. FLAIRS Conference (2003)
Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
Time and sample efficient discovery of Markov blankets and direct causal relations. KDD (2003)
Lewis J. Frey, Douglas H. Fisher, Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
Identifying Markov Blankets with Decision Tree Induction. ICDM (2003)
Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
Algorithms for Large Scale Markov Blanket Discovery. FLAIRS Conference (2003)
Constantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery. METMBS (2003)
Yindalon Aphinyanaphongs, Constantin F. Aliferis
Text Categorization Models for Retrieval of High Quality Articles in Internal Medicine. AMIA (2003)
Constantin F. Aliferis, Ioannis Tsamardinos, Pierre P. Massion, Alexander R. Statnikov, Douglas P. Hardin
Why Classification Models Using Array Gene Expression Data Perform So Well: A Preliminary Investigation of Explanatory Factors. METMBS (2003)
Constantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov
HITON: A Novel Markov Blanket Algorithm for Optimal Variable Selection. AMIA (2003)
Ioannis Tsamardinos, Constantin F. Aliferis
Towards Principled Feature Selection: Relevancy, Filters and Wrappers. AISTATS (2003)
Constantin F. Aliferis, Douglas P. Hardin, Pierre P. Massion
Machine learning models for lung cancer classification using array comparative genomic hybridization. AMIA (2002)
Constantin F. Aliferis, Gregory F. Cooper
Temporal representation design principles: an assessment in the domain of liver transplantation. AMIA (1998)
Constantin F. Aliferis, Gregory F. Cooper, Martha E. Pollack, Bruce G. Buchanan, Michael M. Wagner
Representing and developing temporally abstracted knowledge as a means towards facilitating time modeling in medical decision-support systems. Comput. Biol. Medicine 27 (5) (1997)
Gregory F. Cooper, Constantin F. Aliferis, Richard Ambrosino, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Clark Glymour, Geoffrey J. Gordon, Barbara H. Hanusa, Janine E. Janosky, Christopher Meek, Tom M. Mitchell, Thomas S. Richardson, Peter Spirtes
An evaluation of machine-learning methods for predicting pneumonia mortality. Artif. Intell. Medicine 9 (2) (1997)
Constantin F. Aliferis, Gregory F. Cooper, Randolph A. Miller, Bruce G. Buchanan, Richard Bankowitz, Nunzia Bettinsoli Giuse
Research Paper: A Temporal Analysis of QMR. J. Am. Medical Informatics Assoc. 3 (1) (1996)
Constantin F. Aliferis, Gregory F. Cooper
A Structurally and Temporally Extended Bayesian Belief Network Model: Definitions, Properties, and Modeling Techniques. UAI (1996)
Constantin F. Aliferis, Gregory F. Cooper
An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Using Simulated Data Sets. UAI (1994)