Greg Cooper Publications


A simple electronic medical record system designed for research
Bayesian network models with decision tree analysis for management of childhood malaria in Malawi
Causal and interventional Markov boundaries
Evaluation of eye tracking for a decision support application
Learning Adjustment Sets from Observational and Limited Experimental Data


A Bayesian approach for detecting a disease that is not being modeled
An instance-specific algorithm for learning the structure of causal Bayesian networks containing latent variables
Explicit representation of protein activity states significantly improves causal discovery of protein phosphorylation networks
Exploring novel graphical presentations of clinical data in a Learning Electronic Medical Record
Learning Adjustment Sets from Observational and Limited Experimental Data
Learning Latent Causal Structures with a Redundant Input Neural Network
Leveraging eye tracking to prioritize relevant medical record data Comparative Machine Learning Study
Lung Cancer Survival Prediction Using Instance-Specific Bayesian Networks
On the Completeness of Causal Discovery in the Presence of Latent Confounding with Tiered Background Knowledge


Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis
Learning high-dimensional directed acyclic graphs with mixed data-types
Systematic discovery of the functional impact of somatic genome alterations in individual tumors through tumor-specific causal inference
Systematic discovery of the functional impact of somatic genome alterations in individual tumors through tumor-specific causal inferenc
Tumor-specific causal inference discovers distinct disease mechanisms underlying cancer subtypes
Using machine learning to selectively highlight patient information


Instance-Specific Bayesian Network Structure Learning
Precision Oncology Beyond Targeted Therapy Combining Omics Data with Machine Learning Matches the Majority of Cancer Cells to Effective Therapeutics
Scoring Bayesian networks of mixed variables
The design and evaluation of a Bayesian System for detecting and characterizing outbreaks of influenza
Using Machine Learning to Predict the Information Seeking Behavior of Clinicians Using an Electronic Medical Record System


A Bayesian system to detect and characterize overlapping outbreaks.
A new method for estimating causal model learning accuracy. In Workshop on Data Mining for Medical Informatics DMMI
A study of the transferability of influenza case detection systems between two large healthcare systems
An assessment of the calibration of causal relationships learned using RFCI and bootstrapping
Automated influenza case detection for public health surveillance and clinical diagnosis using dynamic influenza prevalence method
Binary classifier calibration using an ensemble of piecewise linear regression models
Discovery of causal models that contain latent variables through Bayesian scoring of independence constraints
Eye-tracking for clinical decision support A method to capture automatically what physicians are viewing in the EMR
Obtaining Accurate Probabilistic Causal Inference by Post-Processing Calibration
The effects of natural language processing on cross-institutional portability of influenza case detection for disease surveillance
Tumor-specific Causal Inference TCI A Bayesian Method for Identifying Causative Genome Alterations within Individual Tumors


Binary classifier calibration using an ensemble of linear trend estimation
Binary classifier calibration using an ensemble of near isotonic regression models
Inferring Causal Molecular Networks Empirical Assessment through a Community-Based Effort
Outlier-based detection of unusual patient-management actions An ICU study. Journal of Biomedical Informatics
Signal-oriented pathway analyses reveal a signaling complex as a synthetic lethal target for p53 mutations


A Bayesian approach for identifying multivariate differences between groups
A method for detecting and characterizing outbreaks of infectious disease from clinical reports
An efficient pattern mining approach for event detection in multivariate temporal data
Binary classifier calibration using a Bayesian non-parametric approach
Center for Causal Discovery team. The Center for causal discovery of biomedical knowledge from Big Data
Comparison of Machine Learning Classifiers for Influenza Detection from Emergency Department Free-text Reports
Development and preliminary evaluation of a prototype of a learning electronic medical record system
Obtaining well calibrated probabilities using Bayesian binning
Personalized modeling for prediction with decision-path models


A Comparative Analysis of Methods for Predicting Clinical Outcomes Using High-Dimensional Genomic Datasets
Application of Bayesian logistic regression to mining biomedical data


A method for estimating from thermometer sales the incidence of diseases that are symptomatically similar to influenza
A temporal pattern mining approach for classifying electronic health record data
Data-driven identification of unusual clinical actions in the ICU
Decision path models for patient-specific modeling of patient outcomes
Distinct signaling roles of ceramide species in yeast revealed through systematic perturbation and systems biology analyses
Outlier-detection for patient monitoring and alerting


A Bayesian scoring technique for mining predictive and non-spurious rules
A decision-theoretic model of disease surveillance and control and a prototype implementation for the disease influenza
A multivariate probabilistic method for comparing two clinical datasets
Improving the prediction of clinical outcomes from genomic data using multiresolution analysis
Spatial cluster detection using dynamic programming


A Bayesian method for evaluating and discovering disease loci associations
A pattern mining approach for classifying multivariate temporal data
Application of an efficient Bayesian discretization method to biomedical data
Conditional anomaly detection with soft harmonic functions
Probabilistic Case Detection for Disease Surveillance Using Data in Electronic Medical Records
Probabilistic, Decision-theoretic Disease Surveillance and Control


A Bayesian network model for spatial event surveillance
A Bayesian spatio-temporal method for disease outbreak detection
A fast algorithm for learning epistatic genomic relationships
A multivariate Bayesian scan statistic for early event detection and characterization
A new prior for Bayesian anomaly detection – Application to biosurveillance
A real-time temporal Bayesian architecture for event surveillance and its application to patient-specific multiple disease outbreak detection
An efficient Bayesian method for predicting clinical outcomes from genome-wide data
Bayesian rule learning for biomedical data mining
Conditional outlier detection for clinical alerting
Identifying deviations from usual medical care using a statistical approach
Learning instance-specific predictive models
Learning patient-specific predictive models from clinical data
Multivariate Bayesian modeling of known and unknown causes of events – An application to biosurveillance
On the Robustness of Bayesian Network Based Spatial Event Surveillance


Bayesian modeling of unknown disease for biosurveillance
Bayesian prediction of an epidemic curve
Generalized AMOC curves for evaluation and improvement of event surveillance


A temporal method for outbreak detection using a Bayesian networks
Analysis of a failed clinical decision support system for management of congestive heart failure
Chapman W. Analysis of a failed clinical decision support system for management of congestive heart failure
Estimating the joint disease outbreak-detection time when an automated biosurveillance system is augmenting traditional clinical case finding
Evaluation of preprocessing techniques for chief complaint classification
Hierarchical explanation of inference in Bayesian networks that represent a population of independent agents


A Bayesian Biosurveillance Method that Models Unknown Outbreak Diseases
A recursive algorithm for spatial cluster detection
Evidence-based anomaly detection in clinical domains
Issues in applied statistics for public health bioterrorism surveillance using multiple data streams Research needs
The Bayesian aerosol release detector an algorithm for detecting and characterizing outbreaks caused by an atmospheric release of Bacillus anthracis


A controlled study to evaluate a computer-based microarray experiment-design-recommendation system for gene-regulation pathway discovery
A theoretical study of Y structures for causal discovery


A Bayesian spatial scan statistic
A prediction rule to identify low-risk patients with heart failure
Accelerating U.S. EHR adoption How to get there from here
Bayesian biosurveillance using multiple data streams
Deriving the expected utility of a predictive model when the utilities are uncertain
Instance-specific Bayesian model averaging for classification
Predicting dire outcomes of patients with community acquired pneumonia
What’s Strange About Recent Events (WSARE) An algorithm for the early detection of disease outbreaks


An evaluation of a system that recommends microarray experiments to perform to discover gene-regulation pathways
Bayesian biosurveillance of disease outbreaks
Causal discovery using a Bayesian local causal discovery algorithm
Model averaging for prediction with discrete Bayesian networks


A computer-based microarray experiment design-system for gene-regulation pathway discovery
Bayesian network anomaly pattern detection for disease outbreaks
Creating a text classifier to detect radiology reports describing mediastinal findings associated with inhalational anthrax and other disorders
Detecting adverse drug events in discharge summaries using variations on the simple Bayes model
WSARE What’s Strange About Recent Events


A Bayesian network scoring metric that is based on globally uniform parameter priors
A simple algorithm for identifying negated findings and diseases in discharge summaries
Discovery of causal relationships in a gene-regulation pathway from a mixture of experimental and observational DNA microarray data
Discovery of gene-regulation pathways using local causal search
Exact model averaging with naive Bayesian classifiers
Rule-based anomaly pattern detection for detecting disease outbreaks


A simulation study of three related causal data mining algorithms
Evaluation of negation phrases in narrative clinical reports
Piecewise linear instrumental variable estimation of causal influence
Predicting with variables constructed from temporal sequences


A Bayesian method for causal modeling and discovery under selection
Causal discovery from medical textual data
IBIZA E-market infrastructure for custom-built information products
Predicting ICU motality A comparison of stationary and nonstationary temporal models


A Bayesian network classifier that combines a finite mixture model and a naïve Bayes model
A latent variable model for multivariate discretization
A study in causal discovery from population-based infant birth and death records
An experiment in causal discovery using a pneumonia database
Causal discovery from a mixture of experimental and observational data
Identifying patient subgroups with simple Bayes


A multivariate discretization method for learning Bayesian networks from mixed data
An experiment comparing lexical and statistical methods for extracting MeSH terms from clinical free text
Temporal representation design principles An assessment in the domain of liver transplantation
The impact of modeling the dependencies among patient findings on classification accuracy and calibration
Using computer modeling to help identify patient subgroups in clinical data repositories


A simple algorithm for efficiently mining observational databases for causal relationships
An evaluation of machine-learning methods for predicting pneumonia mortality
INKBLOT A neurological diagnostic decision support system integrating causal and anatomical knowledge
Representing and developing temporally abstracted knowledge as a means towards facilitating time modeling in medical decision support systems


A structurally and temporally extended Bayesian belief network model Definitions, properties, and modeling techniques
A temporal analysis of QMR
Bounded recursive decomposition A search-based method for belief-network inference under limited resources
Human causal discovery from observational data
Learning Bayesian belief networks with neural network estimators
Representing CARE rules in a decision-theoretic formalism


A method for learning belief networks that contain hidden variables
A new formalism for temporal modeling in medical decision-support systems
Building a medical multimedia database to integrate clinical information An application of high-performance computing and communications technology
Causal discovery from data in the presence of selection bias
Evaluation of a belief-network-based reminder system that learns from utility feedback
Image Engine An integrated multimedia clinical information system
Temporal reasoning abstractions in QMR
The use of misclassification costs to learn rule-based decision support models for cost-effective hospital admission strategies


A temporal analysis of QMR Abstracted temporal representation and reasoning and initial assessment of diagnostic performance trade-offs
An evaluation of an algorithm for inductive learning of Bayesian belief networks using simulated data sets


A Bayesian method for learning belief networks that contain hidden variables
A prototype expert system for statistical analysis
An evaluation of explanations of probabilistic inference
Decision-theoretic information pretrieval A generalization of reminding
Patient simulation using seamless digital video


A Bayesian method for the induction of probabilistic networks from data
CHARTLINE Providing bibliographic references relevant to patient charts using the UMLS Metathesaurus knowledge sources
Evaluation of a Meta-1-based automatic indexing method for medical documents


A Bayesian method for constructing Bayesian belief networks from databases
A combination of exact algorithms for inference on Bayesian belief networks
Algorithms for Bayesian belief-network precomputation
An empirical analysis of likelihood-weighting simulation on a large, multiply-connected belief network
Building a speech interface to a medical diagnostic system
Initialization for the method of conditioning in Bayesian belief networks
Probabilistic diagnosis using a reformulation of the INTERNIST-1 QMR knowledge base — Evaluation of diagnostic performance
Probabilistic diagnosis using a reformulation of the INTERNIST-1 QMR knowledge base – The probabilistic model and inference algorithms


A combination of cutset conditioning and clique-tree propagation in the Pathfinder system
A probabilistic reformulation of the Quick Medical Reference System
A randomized approximation algorithm for probabilistic inference on Bayesian belief networks
An empirical analysis of likelihood-weighting simulation on a large, multiply-connected belief network
Hypermedia and randomized algorithms for medical expert systems.
KNET Integrating hypermedia and normative Bayesian modeling
Kutató An entropy-driven system for the construction of probabilistic expert systems from databases
Probabilistic inference in multiply connected belief networks using loop cutsets.
The computational complexity of probabilistic inference using Bayesian belief networks.


An algorithm for computing probabilistic propositions.
An empirical evaluation of a randomized algorithm for probabilistic inference.
Bounded conditioning Flexible inference for decisions under scarce resources.
Case-based tutoring from a medical knowledge base.
Reflection and action under scarce resources Theoretical principles and empirical study.
Stochastic simulation of causal Bayesian models.
The ALARM monitoring system A case study with two probabilistic inference techniques for belief networks.


A method for using belief networks as influence diagrams.


A diagnostic method that uses causal knowledge and linear programming in the application of Bayes’ formula.