## 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

2020:

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

2019:

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

2018:

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

2017:

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

2016:

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

2015:

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

2014:

A Comparative Analysis of Methods for Predicting Clinical Outcomes Using High-Dimensional Genomic Datasets

Application of Bayesian logistic regression to mining biomedical data

2013:

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

2012:

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

2011:

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

2010:

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

2009:

Bayesian modeling of unknown disease for biosurveillance

Bayesian prediction of an epidemic curve

Generalized AMOC curves for evaluation and improvement of event surveillance

2008:

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

2007:

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

2006:

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

2005:

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

2004:

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

2003:

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

2002:

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

2001:

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

2000:

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

1999:

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

1998:

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

1997:

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

1996:

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

1995:

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

1994:

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

1993:

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

1992:

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

1991:

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

1990:

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.

1989:

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.

1988:

A method for using belief networks as influence diagrams.

1986: