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Ryan J. Urbanowicz

Observed names: R Urbanowicz, R. Urbanowicz, R.J. Urbanowicz, Ryan J Urbanowicz, Ryan John Urbanowicz, Ryan Urbanowicz, Urbanowicz Ryan J., Urbanowicz, Ryan, Urbanowicz, Ryan J.
ORCID: 0000-0002-0487-5555
Observed ORCID: 0000-0002-0487-5555
OpenAlex ID: A5023718023
Relief-based feature selection: Introduction and review
2018 · Ryan J. Urbanowicz, Melissa Meeker, et al. · Journal of Biomedical Informatics · 1,304
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Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science
2016 · Randal S. Olson, Nathan Bartley, et al. · Genetic and Evolutionary Computation Conference (GECCO) · 594
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ChatGPT and large language models in academia: opportunities and challenges
2023 · Jesse G. Meyer, Ryan J. Urbanowicz, et al. · BioData Mining · 563
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PMLB: a large benchmark suite for machine learning evaluation and comparison
2017 · Randal S. Olson, William La Cava, et al. · BioData Mining · 367
Automating Biomedical Data Science Through Tree-Based Pipeline Optimization
2016 · Randal S. Olson, Ryan J. Urbanowicz, et al. · Lecture notes in computer science · 329
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Learning Classifier Systems: A Complete Introduction, Review, and Roadmap
2009 · Ryan J. Urbanowicz, Jason H. Moore · Journal of Artificial Evolution and Applications · 306
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Benchmarking relief-based feature selection methods for bioinformatics data mining
2018 · Ryan J. Urbanowicz, Randal S. Olson, et al. · Journal of Biomedical Informatics · 253
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GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures
2012 · Ryan J Urbanowicz, Jeff Kiralis, et al. · BioData Mining · 221
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ExSTraCS 2.0: description and evaluation of a scalable learning classifier system
2015 · Ryan J. Urbanowicz, Jason H. Moore · Evolutionary Intelligence · 125
Why Is the Electronic Health Record So Challenging for Research and Clinical Care?
2021 · John H. Holmes, James Beinlich, et al. · Methods of Information in Medicine · 117
Introduction to Learning Classifier Systems
2017 · Ryan J. Urbanowicz, Will N. Browne · SpringerBriefs in intelligent systems · 104
Analysis of Gene‐Gene Interactions
2017 · Brian S. Cole, Molly A. Hall, et al. · Current Protocols in Human Genetics · 78
Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach
2013 · Ryan John Urbanowicz, Angeline S Andrew, et al. · Journal of the American Medical Informatics Association · 67
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Genetic heterogeneity: Challenges, impacts, and methods through an associative lens
2022 · Alexa A. Woodward, Ryan J. Urbanowicz, et al. · Genetic Epidemiology · 66
An analysis pipeline with statistical and visualization-guided knowledge discovery for Michigan-style learning classifier systems
2012 · Ryan J. Urbanowicz, Ambrose Granizo-Mackenzie, et al. · IEEE Computational Intelligence Magazine · 64
STatistical Inference Relief (STIR) feature selection
2018 · Trang T Le, Ryan J Urbanowicz, et al. · Bioinformatics · 61
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The application of michigan-style learning classifiersystems to address genetic heterogeneity and epistasisin association studies
2010 · Ryan J. Urbanowicz, Jason H. Moore · Genetic and Evolutionary Computation Conference (GECCO) · 44
Preparing Next-Generation Scientists for Biomedical Big Data: Artificial Intelligence Approaches
2019 · Jason H Moore, Mary Regina Boland, et al. · Personalized Medicine · 40
Instance-linked attribute tracking and feedback for michigan-style supervised learning classifier systems
2012 · Ryan Urbanowicz, Ambrose Granizo-Mackenzie, et al. · Genetic and Evolutionary Computation Conference (GECCO) · 37
Collective feature selection to identify crucial epistatic variants
2018 · Shefali S. Verma, Anastasia Lucas, et al. · BioData Mining · 34
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Is low-risk status a surrogate outcome in pulmonary arterial hypertension? An analysis of three randomised trials
2023 · Bryan S Blette, Jude Moutchia, et al. · The Lancet Respiratory Medicine · 33
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Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection
2012 · Ryan J Urbanowicz, Jeff Kiralis, et al. · BioData Mining · 32
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Rapid Rule Compaction Strategies for Global Knowledge Discovery in a Supervised Learning Classifier System
2013 · Jie Tan, Jason Moore, et al. · 31
Using Expert Knowledge to Guide Covering and Mutation in a Michigan Style Learning Classifier System to Detect Epistasis and Heterogeneity
2012 · Ryan J. Urbanowicz, Delaney Granizo-Mackenzie, et al. · Lecture notes in computer science · 31
Ideas for how informaticians can get involved with COVID-19 research
2020 · Jason H. Moore, Ian Barnett, et al. · BioData Mining · 29
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Works count: 148
Citation count: 5,431
H-index: 26
I10-index: 42
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