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Ryan J Urbanowicz
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Relief-based feature selection: Introduction and review
RJ Urbanowicz, M Meeker, W La Cava, RS Olson, JH Moore
Journal of biomedical informatics 85, 189-203, 2018
12922018
Evaluation of a tree-based pipeline optimization tool for automating data science
RS Olson, N Bartley, RJ Urbanowicz, JH Moore
Proceedings of the genetic and evolutionary computation conference 2016, 485-492, 2016
7502016
PMLB: a large benchmark suite for machine learning evaluation and comparison
RS Olson, W La Cava, P Orzechowski, RJ Urbanowicz, JH Moore
BioData mining 10, 1-13, 2017
4362017
Learning classifier systems: a complete introduction, review, and roadmap
RJ Urbanowicz, JH Moore
Journal of Artificial Evolution and Applications 2009 (1), 736398, 2009
4062009
Automating biomedical data science through tree-based pipeline optimization
RS Olson, RJ Urbanowicz, PC Andrews, NA Lavender, LC Kidd, ...
Applications of Evolutionary Computation: 19th European Conference …, 2016
3612016
ChatGPT and large language models in academia: opportunities and challenges
JG Meyer, RJ Urbanowicz, PCN Martin, K O’Connor, R Li, PC Peng, ...
BioData Mining 16 (1), 20, 2023
3452023
Benchmarking relief-based feature selection methods for bioinformatics data mining
RJ Urbanowicz, RS Olson, P Schmitt, M Meeker, JH Moore
Journal of biomedical informatics 85, 168-188, 2018
2822018
GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures
RJ Urbanowicz, J Kiralis, NA Sinnott-Armstrong, T Heberling, JM Fisher, ...
BioData mining 5, 1-14, 2012
2482012
Exstracs 2.0: description and evaluation of a scalable learning classifier system
RJ Urbanowicz, JH Moore
Evolutionary intelligence 8, 89-116, 2015
1402015
Introduction to learning classifier systems
RJ Urbanowicz, WN Browne
Springer, 2017
1312017
Analysis of gene‐gene interactions
D Gilbert‐Diamond, JH Moore
Current protocols in human genetics 70 (1), 1.14. 1-1.14. 12, 2011
1062011
Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach
RJ Urbanowicz, AS Andrew, MR Karagas, JH Moore
Journal of the American Medical Informatics Association 20 (4), 603-612, 2013
792013
An analysis pipeline with statistical and visualization-guided knowledge discovery for michigan-style learning classifier systems
RJ Urbanowicz, A Granizo-Mackenzie, JH Moore
IEEE computational intelligence magazine 7 (4), 35-45, 2012
702012
Statistical inference relief (STIR) feature selection
TT Le, RJ Urbanowicz, JH Moore, BA McKinney
Bioinformatics 35 (8), 1358-1365, 2019
672019
Why is the electronic health record so challenging for research and clinical care?
JH Holmes, J Beinlich, MR Boland, KH Bowles, Y Chen, TS Cook, ...
Methods of information in medicine 60 (01/02), 032-048, 2021
562021
Instance-linked attribute tracking and feedback for michigan-style supervised learning classifier systems
R Urbanowicz, A Granizo-Mackenzie, J Moore
Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012
472012
The application of michigan-style learning classifiersystems to address genetic heterogeneity and epistasisin association studies
RJ Urbanowicz, JH Moore
Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010
452010
Preparing next-generation scientists for biomedical big data: artificial intelligence approaches
JH Moore, MR Boland, PG Camara, H Chervitz, G Gonzalez, BE Himes, ...
Personalized medicine 16 (3), 247-257, 2019
402019
Rapid rule compaction strategies for global knowledge discovery in a supervised learning classifier system
J Tan, J Moore, R Urbanowicz
Artificial Life Conference Proceedings, 110-117, 2013
402013
Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection
RJ Urbanowicz, J Kiralis, JM Fisher, JH Moore
BioData mining 5, 1-13, 2012
362012
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