An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Using Simulated Data Sets. - Constantin F. Aliferis; Gregory F. Cooper (UAI, 1994)

A Structurally and Temporally Extended Bayesian Belief Network Model: Definitions, Properties, and Modeling Techniques. - Constantin F. Aliferis; Gregory F. Cooper (UAI, 1996)

Research Paper: A Temporal Analysis of QMR. - Constantin F. Aliferis; Gregory F. Cooper; Randolph A. Miller; Bruce G. Buchanan; Richard Bankowitz; Nunzia Bettinsoli Giuse (J. Am. Medical Informatics Assoc., 1996)

An evaluation of machine-learning methods for predicting pneumonia mortality. - 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; et al. (Artif. Intell. Medicine, 1997)

Representing and developing temporally abstracted knowledge as a means towards facilitating time modeling in medical decision-support systems. - Constantin F. Aliferis; Gregory F. Cooper; Martha E. Pollack; Bruce G. Buchanan; Michael M. Wagner 001 (Comput. Biol. Medicine, 1997)

Temporal representation design principles: an assessment in the domain of liver transplantation. - Constantin F. Aliferis; Gregory F. Cooper (AMIA, 1998)

Machine learning models for lung cancer classification using array comparative genomic hybridization. - Constantin F. Aliferis; Douglas P. Hardin; Pierre P. Massion (AMIA, 2002)

Towards Principled Feature Selection: Relevancy, Filters and Wrappers. - Ioannis Tsamardinos; Constantin F. Aliferis (AISTATS, 2003)

HITON: A Novel Markov Blanket Algorithm for Optimal Variable Selection. - Constantin F. Aliferis; Ioannis Tsamardinos; Alexander R. Statnikov (AMIA, 2003)

Text Categorization Models for Retrieval of High Quality Articles in Internal Medicine. - Yindalon Aphinyanaphongs; Constantin F. Aliferis (AMIA, 2003)

Machine Learning Models for Classification of Lung Cancer and Selection of Genomic Markers Using Array Gene Expression Data. - Constantin F. Aliferis; Ioannis Tsamardinos; Pierre P. Massion; Alexander R. Statnikov; Nafeh Fananapazir; Douglas P. Hardin (FLAIRS, 2003)

Algorithms for Large Scale Markov Blanket Discovery. - Ioannis Tsamardinos; Constantin F. Aliferis; Alexander R. Statnikov (FLAIRS, 2003)

Identifying Markov Blankets with Decision Tree Induction. - Lewis J. Frey; Douglas H. Fisher; Ioannis Tsamardinos; Constantin F. Aliferis; Alexander R. Statnikov (ICDM, 2003)

Time and sample efficient discovery of Markov blankets and direct causal relations. - Ioannis Tsamardinos; Constantin F. Aliferis; Alexander R. Statnikov (KDD, 2003)

Why Classification Models Using Array Gene Expression Data Perform So Well: A Preliminary Investigation of Explanatory Factors. - Constantin F. Aliferis; Ioannis Tsamardinos; Pierre P. Massion; Alexander R. Statnikov; Douglas P. Hardin (METMBS, 2003)

Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery. - Constantin F. Aliferis; Ioannis Tsamardinos; Alexander R. Statnikov; Laura E. Brown (METMBS, 2003)

A theoretical characterization of linear SVM-based feature selection. - Douglas P. Hardin; Ioannis Tsamardinos; Constantin F. Aliferis (ICML, 2004)

Learning Boolean Queries for Article Quality Filtering. - Yin Aphinyanaphongs; Constantin F. Aliferis (MedInfo, 2004)

A Novel Algorithm for Scalable and Accurate Bayesian Network Learning. - Laura E. Brown; Ioannis Tsamardinos; Constantin F. Aliferis (MedInfo, 2004)

Methods for Multi-Category Cancer Diagnosis from Gene Expression Data: A Comprehensive Evaluation to Inform Decision Support System Development. - Alexander R. Statnikov; Constantin F. Aliferis; Ioannis Tsamardinos (MedInfo, 2004)

A Comparison of Novel and State-of-the-Art Polynomial Bayesian Network Learning Algorithms. - Laura E. Brown; Ioannis Tsamardinos; Constantin F. Aliferis (AAAI, 2005)

Using the GEMS System for Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data. - Alexander R. Statnikov; Ioannis Tsamardinos; Constantin F. Aliferis (AAAI, 2005)

Extracting Drug-Drug Interaction Articles from MEDLINE to Improve the Content of Drug Databases. - Stephany Duda; Constantin F. Aliferis; Randolph A. Miller; Alexander R. Statnikov; Kevin B. Johnson (AMIA, 2005)

Formative Evaluation of a Prototype System for Automated Analysis of Mass Spectrometry Data. - Nafeh Fananapazir; M. Li; D. Spentzos; Constantin F. Aliferis (AMIA, 2005)

Modeling Clinical Judgment and Implicit Guideline Compliance in the Diagnosisof Melanomas Using Machine Learning. - Andrea Sboner; Constantin F. Aliferis (AMIA, 2005)

Using the GEMS System for Supervised Analysis of Cancer Microarray Gene Expression Data. - Alexander R. Statnikov; Ioannis Tsamardinos; Constantin F. Aliferis (AMIA, 2005)

A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis. - Alexander R. Statnikov; Constantin F. Aliferis; Ioannis Tsamardinos; Douglas P. Hardin; Shawn Levy (Bioinform., 2005)

GEMS: A system for automated cancer diagnosis and biomarker discovery from microarray gene expression data. - Alexander R. Statnikov; Ioannis Tsamardinos; Yerbolat Dosbayev; Constantin F. Aliferis (Int. J. Medical Informatics, 2005)

Research Paper: Text Categorization Models for High-Quality Article Retrieval in Internal Medicine. - Yindalon Aphinyanaphongs; Ioannis Tsamardinos; Alexander R. Statnikov; Douglas P. Hardin; Constantin F. Aliferis (J. Am. Medical Informatics Assoc., 2005)

Predicting dire outcomes of patients with community acquired pneumonia. - 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 (J. Biomed. Informatics, 2005)

Prospective Validation of Text Categorization Filters for Identifying High-Quality, Content-Specific Articles in MEDLINE. - Yindalon Aphinyanaphongs; Constantin F. Aliferis (AMIA, 2006)

Generating Realistic Large Bayesian Networks by Tiling. - Ioannis Tsamardinos; Alexander R. Statnikov; Laura E. Brown; Constantin F. Aliferis (FLAIRS, 2006)

Research Paper: A Comparison of Citation Metrics to Machine Learning Filters for the Identification of High Quality MEDLINE Documents. - Yindalon Aphinyanaphongs; Alexander R. Statnikov; Constantin F. Aliferis (J. Am. Medical Informatics Assoc., 2006)

Research Paper: Using Citation Data to Improve Retrieval from MEDLINE. - Elmer V. Bernstam; Jorge R. Herskovic; Yindalon Aphinyanaphongs; Constantin F. Aliferis; Madurai G. Sriram; William R. Hersh (J. Am. Medical Informatics Assoc., 2006)

The max-min hill-climbing Bayesian network structure learning algorithm. - Ioannis Tsamardinos; Laura E. Brown; Constantin F. Aliferis (Mach. Learn., 2006)

A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data. - Subramani Mani; Constantin F. Aliferis (AIME, 2007)

Are Random Forests Better than Support Vector Machines for Microarray-Based Cancer Classification? - Alexander R. Statnikov; Constantin F. Aliferis (AMIA, 2007)

Text Categorization Models for Identifying Unproven Cancer Treatments on the Web. - Yindalon Aphinyanaphongs; Constantin F. Aliferis (MedInfo, 2007)

A Comparison of Impact Factor, Clinical Query Filters, and Pattern Recognition Query Filters in Terms of Sensitivity to Topic. - Lawrence D. Fu; Lily Wang 001; Yindalon Aphinyanagphongs; Constantin F. Aliferis (MedInfo, 2007)

Learning Causal and Predictive Clinical Practice Guidelines from Data. - Subramani Mani; Constantin F. Aliferis; Shanthi Krishnaswami; Theodore Kotchen (MedInfo, 2007)

Models for Predicting and Explaining Citation Count of Biomedical Articles. - Lawrence D. Fu; Constantin F. Aliferis (AMIA, 2008)

A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification. - Alexander R. Statnikov; Lily Wang 001; Constantin F. Aliferis (BMC Bioinform., 2008)

Design and Analysis of the Causation and Prediction Challenge. - Isabelle Guyon; Constantin F. Aliferis; Gregory F. Cooper; André Elisseeff; Jean-Philippe Pellet; Peter Spirtes; Alexander R. Statnikov (WCCI Causation and Prediction Challenge, 2008)

The FAST-AIMS Clinical Mass Spectrometry Analysis System. - Nafeh Fananapazir; Alexander R. Statnikov; Constantin F. Aliferis (Adv. Bioinformatics, 2009)

Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation. - Constantin F. Aliferis; Alexander R. Statnikov; Ioannis Tsamardinos; Subramani Mani; Xenofon D. Koutsoukos (J. Mach. Learn. Res., 2010)

Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions. - Constantin F. Aliferis; Alexander R. Statnikov; Ioannis Tsamardinos; Subramani Mani; Xenofon D. Koutsoukos (J. Mach. Learn. Res., 2010)

Bayesian Algorithms for Causal Data Mining. - Subramani Mani; Constantin F. Aliferis; Alexander R. Statnikov (NIPS Causality: Objectives and Assessment, 2010)

TIED: An Artificially Simulated Dataset with Multiple Markov Boundaries. - Alexander R. Statnikov; Constantin F. Aliferis (NIPS Causality: Objectives and Assessment, 2010)

Analysis and Computational Dissection of Molecular Signature Multiplicity. - Alexander R. Statnikov; Constantin F. Aliferis (PLoS Comput. Biol., 2010)

Using content-based and bibliometric features for machine learning models to predict citation counts in the biomedical literature. - Lawrence D. Fu; Constantin F. Aliferis (Scientometrics, 2010)

A comparison of evaluation metrics for biomedical journals, articles, and websites in terms of sensitivity to topic. - Lawrence D. Fu; Yindalon Aphinyanaphongs; Lily Wang 001; Constantin F. Aliferis (J. Biomed. Informatics, 2011)

Time Series Analysis with the Causality Workbench. - Isabelle Guyon; Alexander R. Statnikov; Constantin F. Aliferis (NIPS Mini-Symposium on Causality in Time Series, 2011)

Informaticians, CxIOs and Industry: Strengthening the Fabric of HealthIT. - Titus Schleyer; Blackford Middleton; Bret Shillingstad; J. Marc Overhage; Constantin F. Aliferis (AMIA, 2013)

Identifying Unproven Cancer Treatments on the Health Web: Addressing Accuracy, Generalizability and Scalability. - Yindalon Aphinyanaphongs; Lawrence D. Fu; Constantin F. Aliferis (MedInfo, 2013)

An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Usin - Constantin F. Aliferis; Gregory F. Cooper (CoRR, 2013)

Algorithms for discovery of multiple Markov boundaries. - Alexander R. Statnikov; Jan Lemeire; Constantin F. Aliferis (J. Mach. Learn. Res., 2013)

Computer models for identifying instrumental citations in the biomedical literature. - Lawrence D. Fu; Yindalon Aphinyanaphongs; Constantin F. Aliferis (Scientometrics, 2013)

Medical decision support using machine learning for early detection of late-onset neonatal sepsis. - Subramani Mani; Asli Ozdas; Constantin F. Aliferis; Huseyin Atakan Varol; Qingxia Chen; Randy J. Carnevale; Yukun Chen 001; Joann Romano-Keeler; Hui Nian; Jörn-Hendrik Weitkamp (J. Am. Medical Informatics Assoc., 2014)

A comprehensive empirical comparison of modern supervised classification and feature selection methods for text categorization. - Yindalon Aphinyanaphongs; Lawrence D. Fu; Zhiguo Li; Eric R. Peskin; Efstratios Efstathiadis; Constantin F. Aliferis; Alexander R. Statnikov (J. Assoc. Inf. Sci. Technol., 2014)

Computational Methods for Unraveling Temporal Brain Connectivity Data. - Bisakha Ray; Constantin F. Aliferis; Alexander R. Statnikov (AMIA, 2015)

Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discovery. - Alexander R. Statnikov; Sisi Ma; Mikael Henaff; Nikita I. Lytkin; Efstratios Efstathiadis; Eric R. Peskin; Constantin F. Aliferis (J. Mach. Learn. Res., 2015)

Developing a Clinico-Molecular Test for Individualized Treatment of Ovarian Cancer: The interplay of Precision Medicine Informatics with Clinical and Health Economics Dimensions. - 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; et al. (AMIA, 2018)

Artifacts in spatial transcriptomics data: their detection, importance, prevalence, and prevention. - Erich Kummerfeld; Leland Williams; Yinzhao Wang; Samuel T. Peters; Elizabeth Schmidt; Mickayla Dufresne-To; David Bernlohr; Paul Robbins; Sayeed Ikramuddin; Oyedele Adeyi; Linshan Laux; Grant Barthel; et al. (Briefings Bioinform., 2025)