John M. Aronis

发表

Predicting dire outcomes of patients with community acquired pneumonia

Constantin F. Aliferis, Tom M. Mitchell, Rich Caruana, 2005, J. Biomed. Informatics.

An evaluation of machine-learning methods for predicting pneumonia mortality

Constantin F. Aliferis, Tom M. Mitchell, Rich Caruana, 1997, Artif. Intell. Medicine.

Gender and race in predicting achievement in computer science

Sandra Katz, David Allbritton, Mary Lou Soffa, 2003, IEEE Technol. Soc. Mag..

Efficiently Constructing Relational Features from Background Knowledge for Inductive Machine Learning

Foster J. Provost, John M. Aronis, 1994, KDD Workshop.

Modeling pedagogical interactions with machine learning

Sandra Katz, John M. Aronis, Colin Creitz, 2000, Kognitionswissenschaft.

Hybridizing nonmonotonic inheritance with theorem proving

Richmond H. Thomason, John M. Aronis, R. Thomason, 1992, Annals of Mathematics and Artificial Intelligence.

A Retrospective Study of the Effect of a Prognostic Model on the Hospital Admission Decision for Patients with Low Risk Community-acquired Pneumonia

Gregory F. Cooper, Michael J. Fine, John M. Aronis, 2000, AMIA.

A study to identify predictors of achievement in an introductory computer science course

Sandra Katz, David Allbritton, Mary Lou Soffa, 2003, SIGMIS CPR '03.

Scaling up inductive learning with massive parallelism

Foster J. Provost, John M. Aronis, F. Provost, 2004, Machine Learning.

Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation

Foster J. Provost, John M. Aronis, F. Provost, 1997, KDD.

Knowledge-Based Learning in Exploratory Science: Learning Rules to Predict Rodent Carcinogenicity

Bruce G. Buchanan, Yongwon Lee, John M. Aronis, 1998, Machine Learning.

Scaling Up Inductive Learning with Massive Parallelism

John M. Aronis, Foster John Provost, 2005, Machine Learning.

Assistive Technology and Artificial Intelligence: Applications in Robotics, User Interfaces and Natural Language Processing

Vibhu O. Mittal, Holly A. Yanco, Richard C. Simpson, 1998 .

A Bayesian system to detect and characterize overlapping outbreaks

Ye Ye, Peter J. Haug, Gregory F. Cooper, 2017, J. Biomed. Informatics.

Implementing inheritance with roles on the connection machine

John M. Aronis, 1993 .

A Method for Detecting and Characterizing Multiple Outbreaks of Infectious Diseases

Gregory F. Cooper, Michael M. Wagner, Ye Ye, 2016 .

Gender, achievement, and persistence in an undergraduate computer science program

Sandra Katz, David Allbritton, Mary Lou Soffa, 2006, DATB.

Identifying patient subgroups with simple Bayes'

Bruce G. Buchanan, Gregory F. Cooper, Mehmet Kayaalp, 1999, AMIA.

Assistive Technology and Artificial Intelligence

Vibhu O. Mittal, Holly A. Yanco, Richard C. Simpson, 1998, Lecture Notes in Computer Science.

Exploiting Background Knowledge in Automated Discovery

Foster J. Provost, Bruce G. Buchanan, John M. Aronis, 1996, KDD.

The WoRLD: Knowledge Discovery from Multiple Distributed Databases

Bruce G. Buchanan, Venkateswarlu Kolluri, John M. Aronis, 2007 .

Increasing Diversity in the Information Technology Workforce: Implications from a Study of Factors that Predict Achievement in CS

Sandra Katz, David Allbritton, Mary Lou Soffa, 2004, ICLS.

E ciently Constructing Relational Features from Background Knowledge for Inductive Machine Learning Also appears in Proceedings AAAI-94 Workshop on Knowledge Discovery in Databases

Foster J. Provost, John M. Aronis, 2007 .

The design and evaluation of a Bayesian system for detecting and characterizing outbreaks of influenza

John M. Aronis, Jeffrey P. Ferraro, G. Cooper, 2018, bioRxiv.

The design and evaluation of a Bayesian system for detecting and characterizing outbreaks of inﬂuenza

John M. Aronis, G. Cooper, P. Haug, 2018 .

A Bayesian approach for detecting a disease that is not being modeled

John M. Aronis, Jeffrey P. Ferraro, G. Cooper, 2020, PloS one.