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Constantin F. Aliferis
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2010 – 2019
- 2018
- [c39]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 - 2015
- [j22]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: 3219-3267 (2015) - [c38]Bisakha Ray, Constantin F. Aliferis, Alexander R. Statnikov:
Computational Methods for Unraveling Temporal Brain Connectivity Data. AMIA 2015 - 2014
- [j21]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): 326-336 (2014) - [j20]Yindalon Aphinyanaphongs
A comprehensive empirical comparison of modern supervised classification and feature selection methods for text categorization. J. Assoc. Inf. Sci. Technol. 65(10): 1964-1987 (2014) - 2013
- [j19]Alexander R. Statnikov, Jan Lemeire, Constantin F. Aliferis:
Algorithms for discovery of multiple Markov boundaries. J. Mach. Learn. Res. 14(1): 499-566 (2013) - [j18]Lawrence D. Fu, Yindalon Aphinyanaphongs
Computer models for identifying instrumental citations in the biomedical literature. Scientometrics 97(3): 871-882 (2013) - [c37]Titus Schleyer, Blackford Middleton, Bret Shillingstad, J. Marc Overhage, Constantin F. Aliferis:
Informaticians, CxIOs and Industry: Strengthening the Fabric of HealthIT. AMIA 2013 - [c36]Yindalon Aphinyanaphongs, Lawrence D. Fu, Constantin F. Aliferis:
Identifying Unproven Cancer Treatments on the Health Web: Addressing Accuracy, Generalizability and Scalability. MedInfo 2013: 667-671 - [i2]Constantin F. Aliferis, Gregory F. Cooper:
A Structurally and Temporally Extended Bayesian Belief Network Model: Definitions, Properties, and Modeling Techniques. CoRR abs/1302.3552 (2013) - [i1]Constantin F. Aliferis, Gregory F. Cooper:
An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Usin. CoRR abs/1302.6779 (2013) - 2011
- [j17]Lawrence D. Fu, Yindalon Aphinyanaphongs
A comparison of evaluation metrics for biomedical journals, articles, and websites in terms of sensitivity to topic. J. Biomed. Informatics 44(4): 587-594 (2011) - [c35]Isabelle Guyon, Alexander R. Statnikov, Constantin F. Aliferis:
Time Series Analysis with the Causality Workbench. NIPS Mini-Symposium on Causality in Time Series 2011: 115-139 - 2010
- [j16]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: 171-234 (2010) - [j15]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: 235-284 (2010) - [j14]Alexander R. Statnikov, Constantin F. Aliferis:
Analysis and Computational Dissection of Molecular Signature Multiplicity. PLoS Comput. Biol. 6(5) (2010) - [j13]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): 257-270 (2010) - [c34]Subramani Mani, Constantin F. Aliferis, Alexander R. Statnikov:
Bayesian Algorithms for Causal Data Mining. NIPS Causality: Objectives and Assessment 2010: 121-136 - [c33]Alexander R. Statnikov, Constantin F. Aliferis:
TIED: An Artificially Simulated Dataset with Multiple Markov Boundaries. NIPS Causality: Objectives and Assessment 2010: 249-256
2000 – 2009
- 2009
- [j12]Nafeh Fananapazir, Alexander R. Statnikov, Constantin F. Aliferis:
The FAST-AIMS Clinical Mass Spectrometry Analysis System. Adv. Bioinformatics 2009: 598241:1-598241:4 (2009) - 2008
- [j11]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) - [c32]Lawrence D. Fu, Constantin F. Aliferis:
Models for Predicting and Explaining Citation Count of Biomedical Articles. AMIA 2008 - [c31]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: 1-33 - [e1]Isabelle Guyon, Constantin F. Aliferis, Gregory F. Cooper, André Elisseeff, Jean-Philippe Pellet, Peter Spirtes, Alexander R. Statnikov:
Causation and Prediction Challenge at WCCI 2008, Hong Kong, June 1-6, 2008. JMLR Proceedings 3, JMLR.org 2008 [contents] - 2007
- [c30]Subramani Mani, Constantin F. Aliferis:
A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data. AIME 2007: 446-450 - [c29]Alexander R. Statnikov, Constantin F. Aliferis:
Are Random Forests Better than Support Vector Machines for Microarray-Based Cancer Classification? AMIA 2007 - [c28]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: 716-720 - [c27]Subramani Mani, Constantin F. Aliferis, Shanthi Krishnaswami, Theodore Kotchen:
Learning Causal and Predictive Clinical Practice Guidelines from Data. MedInfo 2007: 850-854 - [c26]Yindalon Aphinyanaphongs, Constantin F. Aliferis:
Text Categorization Models for Identifying Unproven Cancer Treatments on the Web. MedInfo 2007: 968-972 - 2006
- [j10]Elmer V. Bernstam, Jorge R. Herskovic
Research Paper: Using Citation Data to Improve Retrieval from MEDLINE. J. Am. Medical Informatics Assoc. 13(1): 96-105 (2006) - [j9]Yindalon Aphinyanaphongs
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): 446-455 (2006) - [j8]Ioannis Tsamardinos, Laura E. Brown, Constantin F. Aliferis:
The max-min hill-climbing Bayesian network structure learning algorithm. Mach. Learn. 65(1): 31-78 (2006) - [c25]Yindalon Aphinyanaphongs, Constantin F. Aliferis:
Prospective Validation of Text Categorization Filters for Identifying High-Quality, Content-Specific Articles in MEDLINE. AMIA 2006 - [c24]Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown, Constantin F. Aliferis:
Generating Realistic Large Bayesian Networks by Tiling. FLAIRS 2006: 592-597 - 2005
- [j7]Alexander R. Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos, Douglas P. Hardin
A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis. Bioinform. 21(5): 631-643 (2005) - [j6]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): 491-503 (2005) - [j5]Yindalon Aphinyanaphongs
Research Paper: Text Categorization Models for High-Quality Article Retrieval in Internal Medicine. J. Am. Medical Informatics Assoc. 12(2): 207-216 (2005) - [j4]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): 347-366 (2005) - [c23]Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis:
A Comparison of Novel and State-of-the-Art Polynomial Bayesian Network Learning Algorithms. AAAI 2005: 739-745 - [c22]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: 1710-1711 - [c21]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 - [c20]Nafeh Fananapazir, M. Li, D. Spentzos, Constantin F. Aliferis:
Formative Evaluation of a Prototype System for Automated Analysis of Mass Spectrometry Data. AMIA 2005 - [c19]Andrea Sboner, Constantin F. Aliferis:
Modeling Clinical Judgment and Implicit Guideline Compliance in the Diagnosisof Melanomas Using Machine Learning. AMIA 2005 - [c18]Alexander R. Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis:
Using the GEMS System for Supervised Analysis of Cancer Microarray Gene Expression Data. AMIA 2005 - 2004
- [c17]Douglas P. Hardin, Ioannis Tsamardinos, Constantin F. Aliferis:
A theoretical characterization of linear SVM-based feature selection. ICML 2004 - [c16]Yin Aphinyanaphongs, Constantin F. Aliferis:
Learning Boolean Queries for Article Quality Filtering. MedInfo 2004: 263-267 - [c15]Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis:
A Novel Algorithm for Scalable and Accurate Bayesian Network Learning. MedInfo 2004: 711-715 - [c14]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: 813-817 - 2003
- [c13]Ioannis Tsamardinos, Constantin F. Aliferis:
Towards Principled Feature Selection: Relevancy, Filters and Wrappers. AISTATS 2003: 300-307 - [c12]Constantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov:
HITON: A Novel Markov Blanket Algorithm for Optimal Variable Selection. AMIA 2003 - [c11]Yindalon Aphinyanaphongs, Constantin F. Aliferis:
Text Categorization Models for Retrieval of High Quality Articles in Internal Medicine. AMIA 2003 - [c10]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 2003: 67-71 - [c9]Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov:
Algorithms for Large Scale Markov Blanket Discovery. FLAIRS 2003: 376-381 - [c8]Lewis J. Frey, Douglas H. Fisher, Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov:
Identifying Markov Blankets with Decision Tree Induction. ICDM 2003: 59-66 - [c7]Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov:
Time and sample efficient discovery of Markov blankets and direct causal relations. KDD 2003: 673-678 - [c6]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: 47-53 - [c5]Constantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown:
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery. METMBS 2003: 371-376 - 2002
- [c4]Constantin F. Aliferis, Douglas P. Hardin, Pierre P. Massion:
Machine learning models for lung cancer classification using array comparative genomic hybridization. AMIA 2002
1990 – 1999
- 1998
- [c3]Constantin F. Aliferis, Gregory F. Cooper:
Temporal representation design principles: an assessment in the domain of liver transplantation. AMIA 1998 - 1997
- [j3]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): 107-138 (1997) - [j2]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): 411-434 (1997) - 1996
- [j1]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): 79-91 (1996) - [c2]Constantin F. Aliferis, Gregory F. Cooper:
A Structurally and Temporally Extended Bayesian Belief Network Model: Definitions, Properties, and Modeling Techniques. UAI 1996: 28-39 - 1994
- [c1]Constantin F. Aliferis, Gregory F. Cooper:
An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Using Simulated Data Sets. UAI 1994: 8-14
Coauthor Index
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