| 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 | 451 | 2017 |
| Contemporary symbolic regression methods and their relative performance W La Cava, B Burlacu, M Virgolin, M Kommenda, P Orzechowski, ... Advances in neural information processing systems 2021 (DB1), 1, 2021 | 300 | 2021 |
| Where are we now? A large benchmark study of recent symbolic regression methods P Orzechowski, W La Cava, JH Moore Proceedings of the genetic and evolutionary computation conference, 1183-1190, 2018 | 212 | 2018 |
| Benchmarking in optimization: Best practice and open issues T Bartz-Beielstein, C Doerr, D Berg, J Bossek, S Chandrasekaran, ... arXiv preprint arXiv:2007.03488, 2020 | 142 | 2020 |
| Mapping patient trajectories using longitudinal extraction and deep learning in the MIMIC-III critical care database BK Beaulieu-Jones, P Orzechowski, JH Moore Pacific symposium on biocomputing 2018: proceedings of the pacific symposium …, 2018 | 69 | 2018 |
| Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure A Orlenko, JH Moore, P Orzechowski, RS Olson, J Cairns, PJ Caraballo, ... PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018: Proceedings of the Pacific Symposium …, 2018 | 42 | 2018 |
| EBIC: an evolutionary-based parallel biclustering algorithm for pattern discovery P Orzechowski, M Sipper, X Huang, JH Moore Bioinformatics 34 (21), 3719-3726, 2018 | 40 | 2018 |
| A system for accessible artificial intelligence RS Olson, M Sipper, WL Cava, S Tartarone, S Vitale, W Fu, ... Genetic programming theory and practice XV, 121-134, 2018 | 35 | 2018 |
| Text mining with hybrid biclustering algorithms P Orzechowski, K Boryczko International Conference on Artificial Intelligence and Soft Computing, 102-113, 2016 | 25 | 2016 |
| runibic: a Bioconductor package for parallel row-based biclustering of gene expression data P Orzechowski, A Pańszczyk, X Huang, JH Moore Bioinformatics 34 (24), 4302-4304, 2018 | 23 | 2018 |
| Scalable biclustering—the future of big data exploration? P Orzechowski, K Boryczko, JH Moore GigaScience 8 (7), giz078, 2019 | 17 | 2019 |
| Proximity measures and results validation in biclustering–a survey P Orzechowski Artificial Intelligence and Soft Computing: 12th International Conference …, 2013 | 17 | 2013 |
| Contemporary symbolic regression methods and their relative performance, 2021 W La Cava, P Orzechowski, B Burlacu, FO de França, M Virgolin, Y Jin, ... URL https://arxiv. org/abs/2107.14351, 2021 | 15 | 2021 |
| Hybrid biclustering algorithms for data mining P Orzechowski, K Boryczko Applications of Evolutionary Computation: 19th European Conference …, 2016 | 15 | 2016 |
| Propagation-based biclustering algorithm for extracting inclusion-maximal motifs P Orzechowski, K Boryczko Computing and Informatics 35 (2), 391-410, 2016 | 14 | 2016 |
| Artificial Intelligence for COVID-19 Detection in Medical Imaging—Diagnostic Measures and Wasting—A Systematic Umbrella Review P Jemioło, D Storman, P Orzechowski Journal of Clinical Medicine 11 (7), 2054, 2022 | 12 | 2022 |
| EBIC: an open source software for high-dimensional and big data analyses P Orzechowski, JH Moore Bioinformatics 35 (17), 3181-3183, 2019 | 12 | 2019 |
| Vascular phenotypes in early hypertension EC Murray, C Delles, P Orzechowski, P Renc, A Sitek, J Wagenaar, ... Journal of Human Hypertension 37 (10), 898-906, 2023 | 11 | 2023 |
| Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiers P Orzechowski, JH Moore Science Advances 8 (47), eabl4747, 2022 | 11 | 2022 |
| Expanding Polygenic Risk Scores to Include Automatic Genotype Encodings and Gene-gene Interactions. TT Le, H Gong, P Orzechowski, E Manduchi, JH Moore BIOINFORMATICS, 79-84, 2020 | 10 | 2020 |
Jason H. MooreChair, Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CAVerified email at csmc.edu
