default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJason H. Moore
Person information
- affiliation (since 2015): University of Pennsylvania, Computational Genetics Laboratory, Philadelphia, PA, USA
- affiliation (2004-2015): Dartmouth College, Hanover, NH, USA
- affiliation (1999-2004): Vanderbilt University, Nashville, TN, USA
- affiliation (PhD 1999): University of Michigan, Ann Arbor, MI, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j172]Sandra Batista, Vered Madar, Philip J. Freda
, Priyanka Bhandary, Attri Ghosh, Nicholas Matsumoto, Apurva S. Chitre, Abraham A. Palmer, Jason H. Moore:
Interaction models matter: an efficient, flexible computational framework for model-specific investigation of epistasis. BioData Min. 17(1) (2024)- [j171]Bojian Hou, Zixuan Wen, Jingxuan Bao, Richard Zhang, Boning Tong, Shu Yang, Junhao Wen, Yuhan Cui, Jason H. Moore, Andrew J. Saykin, Heng Huang, Paul M. Thompson, Marylyn D. Ritchie, Christos Davatzikos, Li Shen:
Interpretable deep clustering survival machines for Alzheimer's disease subtype discovery. Medical Image Anal. 97: 103231 (2024) - [j170]Emily Wong, Ryan J. Urbanowicz, Tiffani J. Bright, Nicholas P. Tatonetti, Yi-Wen Hsiao, Xiuzhen Huang, Jason H. Moore, Pei-Chen Peng:
Advancing LGBTQ+ inclusion in STEM education and AI research. Patterns 5(6): 101010 (2024) - [c176]Jose Guadalupe Hernandez, Anil Kumar Saini, Jason H. Moore:
Lexidate: Model Evaluation and Selection with Lexicase. GECCO Companion 2024: 279-282 - [c175]Alexa A. Woodward, Harsh Bandhey, Jason H. Moore, Ryan J. Urbanowicz:
Survival-LCS: A Rule-Based Machine Learning Approach to Survival Analysis. GECCO 2024 - [i47]Yu-Ning Huang, Michael I. Love, Cynthia Flaire Ronkowski, Dhrithi Deshpande, Lynn M. Schriml, Annie Wong-Beringer, Barend Mons, Russell Corbett-Detig, Christopher I Hunter, Jason H. Moore, Lana X. Garmire, T. B. K. Reddy, Winston A. Hide, Atul J. Butte, Mark D. Robinson, Serghei Mangul:
Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies. CoRR abs/2401.02965 (2024) - [i46]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
New Pathways in Coevolutionary Computation. CoRR abs/2401.10515 (2024) - [i45]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Coevolving Artistic Images Using OMNIREP. CoRR abs/2401.11167 (2024) - [i44]Moshe Sipper, Jason H. Moore:
Genetic Programming Theory and Practice: A Fifteen-Year Trajectory. CoRR abs/2402.00425 (2024) - [i43]Jun Yu, Yutong Dai, Xiaokang Liu, Jin Huang, Yishan Shen, Ke Zhang, Rong Zhou, Eashan Adhikarla, Wenxuan Ye, Yixin Liu, Zhaoming Kong, Kai Zhang, Yilong Yin, Vinod Namboodiri, Brian D. Davison, Jason H. Moore, Yong Chen:
Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras. CoRR abs/2404.18961 (2024) - [i42]Jose Guadalupe Hernandez, Anil Kumar Saini, Jason H. Moore:
Lexidate: Model Evaluation and Selection with Lexicase. CoRR abs/2406.12006 (2024) - [i41]Sisi Shao, Pedro Henrique Ribeiro, Christina Ramirez, Jason H. Moore:
A review of feature selection strategies utilizing graph data structures and knowledge graphs. CoRR abs/2406.14864 (2024) - [i40]Jose Guadalupe Hernandez, Anil Kumar Saini, Jason H. Moore:
Lexicase Selection Parameter Analysis: Varying Population Size and Test Case Redundancy with Diagnostic Metrics. CoRR abs/2407.15056 (2024) - 2023
- [j169]Abdulrahman Alasiri, Konrad J. Karczewski, Brian S. Cole, Bao-Li Loza, Jason H. Moore, Sander W. Van der Laan, Folkert W. Asselbergs, Brendan J. Keating, Jessica van Setten:
LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants and genes. BioData Min. 16(1) (2023) - [j168]Philip J. Freda, Attri Ghosh, Elizabeth Zhang, Tianhao Luo, Apurva S. Chitre, Oksana Polesskaya, Celine L. St. Pierre, Jianjun Gao, Connor D. Martin, Hao Chen, Angel G. Garcia-Martinez, Tengfei Wang, Wenyan Han, Keita Ishiwari, Paul Meyer, Alexander Lamparelli, Christopher P. King, Abraham A. Palmer, Ruowang Li, Jason H. Moore:
Automated quantitative trait locus analysis (AutoQTL). BioData Min. 16(1) (2023) - [j167]John T. Gregg, Jason H. Moore:
STAR_outliers: a python package that separates univariate outliers from non-normal distributions. BioData Min. 16(1) (2023) - [j166]Jesse G. Meyer, Ryan J. Urbanowicz, Patrick C. N. Martin, Karen O'Connor, Ruowang Li, Pei-Chen Peng, Tiffani J. Bright, Nicholas P. Tatonetti, Kyoung-Jae Won, Graciela Gonzalez-Hernandez, Jason H. Moore:
ChatGPT and large language models in academia: opportunities and challenges. BioData Min. 16(1) (2023) - [j165]Scott M. Williams, Jason H. Moore:
Genetics and precision health: the ecological fallacy and artificial intelligence solutions. BioData Min. 16(1) (2023) - [j164]Hyunjun Choi, Jay Moran, Nicholas Matsumoto, Miguel E. Hernandez, Jason H. Moore:
Aliro: an automated machine learning tool leveraging large language models. Bioinform. 39(10) (2023) - [j163]Jason H. Moore:
Is the evolution metaphor still necessary or even useful for genetic programming? Genet. Program. Evolvable Mach. 24(2): 21 (2023) - [j162]William G. La Cava, Paul C. Lee, Imran Ajmal, Xiruo Ding, Priyanka Solanki, Jordana B. Cohen, Jason H. Moore, Daniel S. Herman:
A flexible symbolic regression method for constructing interpretable clinical prediction models. npj Digit. Medicine 6 (2023) - [j161]Casey-Tyler Berezin, Luis U. Aguilera, Sonja Billerbeck, Philip E. Bourne, Douglas Densmore, Paul S. Freemont, Thomas E. Gorochowski, Sarah I. Hernandez, Nathan J. Hillson, Connor R. King, Michael Köpke, Shuyi Ma, Katie M. Miller, Tae Seok Moon, Jason H. Moore, Brian Munsky, Chris J. Myers, Dequina A. Nicholas, Samuel J. Peccoud, Wen Zhou, Jean Peccoud:
Ten simple rules for managing laboratory information. PLoS Comput. Biol. 19(12) (2023) - [c174]Nicholas Matsumoto, Anil Kumar Saini, Pedro Henrique Ribeiro, Hyunjun Choi, Alena Orlenko, Leo-Pekka Lyytikäinen, Jari O. Laurikka, Terho Lehtimäki, Sandra Batista, Jason H. Moore:
Faster Convergence with Lexicase Selection in Tree-Based Automated Machine Learning. EuroGP 2023: 165-181 - [c173]Rachit Kumar, Joseph D. Romano, Marylyn D. Ritchie, Jason H. Moore:
Extending Tree-Based Automated Machine Learning to Biomedical Image and Text Data Using Custom Feature Extractors. GECCO Companion 2023: 599-602 - [c172]Pedro Henrique Ribeiro, Anil Kumar Saini, Jay Moran, Nicholas Matsumoto, Hyunjun Choi, Miguel E. Hernandez, Jason H. Moore:
TPOT2: A New Graph-Based Implementation of the Tree-Based Pipeline Optimization Tool for Automated Machine Learning. GPTP 2023: 1-17 - [c171]Boning Tong, Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Andrew J. Saykin, Jason H. Moore, Marylyn D. Ritchie, Li Shen:
Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection. MLMI@MICCAI (2) 2023: 144-154 - [i39]Nicholas Matsumoto, Anil Kumar Saini, Pedro Henrique Ribeiro, Hyunjun Choi, Alena Orlenko, Leo-Pekka Lyytikäinen, Jari O. Laurikka, Terho Lehtimäki, Sandra Batista, Jason H. Moore:
Faster Convergence with Lexicase Selection in Tree-based Automated Machine Learning. CoRR abs/2302.00731 (2023) - 2022
- [j160]Carlo Combi, Beatrice Amico, Riccardo Bellazzi, Andreas Holzinger, Jason H. Moore, Marinka Zitnik, John H. Holmes:
A manifesto on explainability for artificial intelligence in medicine. Artif. Intell. Medicine 133: 102423 (2022) - [j159]Philip J. Freda, Henry R. Kranzler, Jason H. Moore:
Novel digital approaches to the assessment of problematic opioid use. BioData Min. 15(1) (2022) - [j158]Roland Albert A. Romero, Mariefel Nicole Y. Deypalan, Suchit Mehrotra, John Titus Jungao, Natalie E. Sheils, Elisabetta Manduchi, Jason H. Moore:
Benchmarking AutoML frameworks for disease prediction using medical claims. BioData Min. 15(1) (2022) - [j157]Alexa A. Woodward, Deanne M. Taylor, Elizabeth Goldmuntz, Laura E. Mitchell, A. J. Agopian, Jason H. Moore, Ryan J. Urbanowicz:
Gene-Interaction-Sensitive enrichment analysis in congenital heart disease. BioData Min. 15(1) (2022) - [j156]Joseph D. Romano, Trang T. Le, William G. La Cava, John T. Gregg, Daniel J. Goldberg, Praneel Chakraborty, Natasha L. Ray, Daniel S. Himmelstein, Weixuan Fu, Jason H. Moore:
PMLB v1.0: an open-source dataset collection for benchmarking machine learning methods. Bioinform. 38(3): 878-880 (2022) - [j155]Xuan Wang, Harrison G. Zhang, Xin Xiong, Chuan Hong, Griffin M. Weber, Gabriel A. Brat, Clara-Lea Bonzel, Yuan Luo, Rui Duan, Nathan P. Palmer, Meghan R. Hutch, Alba Gutiérrez-Sacristán, Riccardo Bellazzi, Luca Chiovato, Kelly Cho, Arianna Dagliati, Hossein Estiri, Noelia García-Barrio, Romain Griffier, David A. Hanauer, Yuk-Lam Ho, John H. Holmes, Mark S. Keller, Jeffrey G. Klann, Sehi L'Yi, Sara Lozano-Zahonero, Sarah E. Maidlow, Adeline Makoudjou, Alberto Malovini, Bertrand Moal, Jason H. Moore, Michele Morris, Danielle L. Mowery, Shawn N. Murphy, Antoine Neuraz, Kee Yuan Ngiam, Gilbert S. Omenn, Lav P. Patel, Miguel Pedrera-Jiménez, Andrea Prunotto, Malarkodi J. Samayamuthu, Fernando J. Sanz Vidorreta, Emily Schriver, Petra Schubert, Pablo Serrano-Balazote, Andrew M. South, Amelia L. M. Tan, Byorn W. L. Tan, Valentina Tibollo, Patric Tippmann, Shyam Visweswaran, Zongqi Xia, William Yuan, Daniela Zöller, Isaac S. Kohane, Paul Avillach, Zijian Guo, Tianxi Cai:
SurvMaximin: Robust federated approach to transporting survival risk prediction models. J. Biomed. Informatics 134: 104176 (2022) - [j154]Mateusz Godzik, Jacek Dajda, Marek Kisiel-Dorohinicki, Aleksander Byrski, Leszek Rutkowski, Patryk Orzechowski, Joost Wagenaar, Jason H. Moore:
Applying autonomous hybrid agent-based computing to difficult optimization problems. J. Comput. Sci. 64: 101858 (2022) - [j153]Mansu Kim, Eun Jeong Min, Kefei Liu, Jingwen Yan, Andrew J. Saykin, Jason H. Moore, Qi Long, Li Shen:
Multi-task learning based structured sparse canonical correlation analysis for brain imaging genetics. Medical Image Anal. 76: 102297 (2022) - [j152]Yun Hao, Joseph D. Romano, Jason H. Moore:
Knowledge-guided deep learning models of drug toxicity improve interpretation. Patterns 3(9): 100565 (2022) - [j151]Jason L. Causey, Keyu Li, Xianghao Chen, Wei Dong, Karl Walker, Jake A. Qualls, Jonathan Stubblefield, Jason H. Moore, Yuanfang Guan, Xiuzhen Huang:
Spatial Pyramid Pooling With 3D Convolution Improves Lung Cancer Detection. IEEE ACM Trans. Comput. Biol. Bioinform. 19(2): 1165-1172 (2022) - [j150]Elisabetta Manduchi, Trang T. Le, Weixuan Fu, Jason H. Moore:
Genetic Analysis of Coronary Artery Disease Using Tree-Based Automated Machine Learning Informed By Biology-Based Feature Selection. IEEE ACM Trans. Comput. Biol. Bioinform. 19(3): 1379-1386 (2022) - [c170]Jiahang Sha, Jingxuan Bao, Kefei Liu, Shu Yang, Zixuan Wen, Yuhan Cui, Junhao Wen, Christos Davatzikos, Jason H. Moore, Andrew J. Saykin, Qi Long, Li Shen:
Preference Matrix Guided Sparse Canonical Correlation Analysis for Genetic Study of Quantitative Traits in Alzheimer's Disease. BIBM 2022: 541-548 - [c169]Patryk Orzechowski, Pawel Renc, William G. La Cava, Jason H. Moore, Arkadiusz Sitek, Jaroslaw Was, Joost Wagenaar:
A comparative study of GP-based and state-of-the-art classifiers on a synthetic machine learning benchmark. GECCO Companion 2022: 276-279 - [i38]Moshe Sipper, Jason H. Moore:
Symbolic-Regression Boosting. CoRR abs/2206.12082 (2022) - [i37]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Solution and Fitness Evolution (SAFE): Coevolving Solutions and Their Objective Functions. CoRR abs/2206.12707 (2022) - [i36]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Solution and Fitness Evolution (SAFE): A Study of Multiobjective Problems. CoRR abs/2206.13509 (2022) - [i35]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Automatically Balancing Model Accuracy and Complexity using Solution and Fitness Evolution (SAFE). CoRR abs/2206.15409 (2022) - [i34]Mateusz Godzik, Jacek Dajda, Marek Kisiel-Dorohinicki, Aleksander Byrski, Leszek Rutkowski, Patryk Orzechowski, Joost Wagenaar, Jason H. Moore:
Applying Autonomous Hybrid Agent-based Computing to Difficult Optimization Problems. CoRR abs/2210.13205 (2022) - [i33]Pedro Henrique Ribeiro, Patryk Orzechowski, Joost Wagenaar, Jason H. Moore:
Benchmarking AutoML algorithms on a collection of synthetic classification problems. CoRR abs/2212.02704 (2022) - 2021
- [j149]Jason H. Moore:
Empowering the data science scientist. BioData Min. 14(1): 8 (2021) - [j148]Alena Orlenko, Jason H. Moore:
A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions. BioData Min. 14(1): 9 (2021) - [j147]Jason H. Moore, Van Q. Truong, Ashley B. Robbins, David Nicholson, Clar Lynda Williams-Devane:
Ten important roles for academic leaders to promote equity, diversity, and inclusion in data science. BioData Min. 14(1): 22 (2021) - [j146]William G. La Cava, Heather Williams, Weixuan Fu, Steven Vitale, Durga Srivatsan, Jason H. Moore:
Evaluating recommender systems for AI-driven biomedical informatics. Bioinform. 37(2): 250-256 (2021) - [j145]Trang T. Le, Jason H. Moore:
treeheatr: an R package for interpretable decision tree visualizations. Bioinform. 37(2): 282-284 (2021) - [j144]Joseph D. Romano, Trang T. Le, Weixuan Fu, Jason H. Moore:
TPOT-NN: augmenting tree-based automated machine learning with neural network estimators. Genet. Program. Evolvable Mach. 22(2): 207-227 (2021) - [j143]Moshe Sipper, Jason H. Moore:
Symbolic-regression boosting. Genet. Program. Evolvable Mach. 22(3): 357-381 (2021) - [j142]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
A semantic genetic programming framework based on dynamic targets. Genet. Program. Evolvable Mach. 22(4): 463-493 (2021) - [j141]Subha Madhavan, Lisa Bastarache, Jeffrey S. Brown, Atul J. Butte, David A. Dorr, Peter J. Embí, Charles P. Friedman, Kevin B. Johnson, Jason H. Moore, Isaac S. Kohane, Philip R. O. Payne, Jessica D. Tenenbaum, Mark G. Weiner, Adam B. Wilcox, Lucila Ohno-Machado:
Use of electronic health records to support a public health response to the COVID-19 pandemic in the United States: a perspective from 15 academic medical centers. J. Am. Medical Informatics Assoc. 28(2): 393-401 (2021) - [j140]Jeffrey G. Klann, Hossein Estiri, Griffin M. Weber, Bertrand Moal, Paul Avillach, Chuan Hong, Amelia L. M. Tan, Brett K. Beaulieu-Jones, Victor M. Castro, Thomas Maulhardt, Alon Geva, Alberto Malovini, Andrew M. South, Shyam Visweswaran, Michele Morris, Malarkodi J. Samayamuthu, Gilbert S. Omenn, Kee Yuan Ngiam, Kenneth D. Mandl, Martin Boeker, Karen L. Olson, Danielle L. Mowery, Robert W. Follett, David A. Hanauer, Riccardo Bellazzi, Jason H. Moore, Ne-Hooi Will Loh, Douglas S. Bell, Kavishwar B. Wagholikar, Luca Chiovato, Valentina Tibollo, Siegbert Rieg, Anthony L. L. J. Li, Vianney Jouhet, Emily Schriver, Zongqi Xia, Meghan Hutch, Yuan Luo, Isaac S. Kohane, Gabriel A. Brat, Shawn N. Murphy:
Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data. J. Am. Medical Informatics Assoc. 28(7): 1411-1420 (2021) - [j139]Yun Hao, Jason H. Moore:
TargetTox: A Feature Selection Pipeline for Identifying Predictive Targets Associated with Drug Toxicity. J. Chem. Inf. Model. 61(11): 5386-5394 (2021) - [j138]John T. Gregg, Trang T. Le, Jason H. Moore:
REGENS: an open source Python package for simulating realistic autosomal genotypes. J. Open Source Softw. 6(59): 2743 (2021) - [j137]Mary Regina Boland, Lena M. Davidson, Silvia P. Canelón, Jessica R. Meeker, Trevor M. Penning, John H. Holmes, Jason H. Moore:
Harnessing electronic health records to study emerging environmental disasters: a proof of concept with perfluoroalkyl substances (PFAS). npj Digit. Medicine 4 (2021) - [c168]Pawel Renc, Patryk Orzechowski, Aleksander Byrski, Jaroslaw Was, Jason H. Moore:
Rapid prototyping of evolution-driven biclustering methods in Julia. GECCO Companion 2021: 61-62 - [c167]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
Towards effective GP multi-class classification based on dynamic targets. GECCO 2021: 812-821 - [c166]Pawel Renc, Patryk Orzechowski, Aleksander Byrski, Jaroslaw Was, Jason H. Moore:
EBIC.JL: an efficient implementation of evolutionary biclustering algorithm in Julia. GECCO Companion 2021: 1540-1548 - [c165]Aleksandra Urbanczyk, Bartosz Nowak, Patryk Orzechowski, Jason H. Moore, Marek Kisiel-Dorohinicki, Aleksander Byrski:
Socio-cognitive Evolution Strategies. ICCS (2) 2021: 329-342 - [c164]William G. La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabrício Olivetti de França, Marco Virgolin, Ying Jin, Michael Kommenda, Jason H. Moore:
Contemporary Symbolic Regression Methods and their Relative Performance. NeurIPS Datasets and Benchmarks 2021 - [c163]Carly A. Bobak, Marek Svoboda, Kristine A. Giffin, Dennis P. Wall, Jason H. Moore:
Raising the stakeholders: Improving patient outcomes through interprofessional collaborations in AI for healthcare. PSB 2021 - [c162]Dokyoon Kim, Ju Han Kim, Jason H. Moore:
Translational Bioinformatics: Integrating Electronic Health Record and Omics Data. PSB 2021 - [i32]Pawel Renc, Patryk Orzechowski, Aleksander Byrski, Jaroslaw Was, Jason H. Moore:
EBIC.JL - an Efficient Implementation of Evolutionary Biclustering Algorithm in Julia. CoRR abs/2105.01196 (2021) - [i31]Patryk Orzechowski, Jason H. Moore:
Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiers. CoRR abs/2107.06475 (2021) - [i30]Roland Albert A. Romero, Mariefel Nicole Y. Deypalan, Suchit Mehrotra, John Titus Jungao, Natalie E. Sheils, Elisabetta Manduchi, Jason H. Moore:
Benchmarking AutoML Frameworks for Disease Prediction Using Medical Claims. CoRR abs/2107.10495 (2021) - [i29]William G. La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabrício Olivetti de França, Marco Virgolin, Ying Jin, Michael Kommenda, Jason H. Moore:
Contemporary Symbolic Regression Methods and their Relative Performance. CoRR abs/2107.14351 (2021) - 2020
- [j136]Jason H. Moore, Randal S. Olson, Peter Schmitt, Yong Chen, Elisabetta Manduchi:
How Computational Experiments Can Improve Our Understanding of the Genetic Architecture of Common Human Diseases. Artif. Life 26(1): 23-37 (2020) - [j135]Jason H. Moore, Ian Barnett, Mary Regina Boland, Yong Chen, George Demiris, Graciela Gonzalez-Hernandez, Daniel S. Herman, Blanca E. Himes, Rebecca A. Hubbard, Dokyoon Kim, Jeffrey S. Morris, Danielle L. Mowery, Marylyn D. Ritchie, Li Shen, Ryan J. Urbanowicz, John H. Holmes:
Ideas for how informaticians can get involved with COVID-19 research. BioData Min. 13(1): 3 (2020) - [j134]Moshe Sipper, Jason H. Moore:
Conservation machine learning. BioData Min. 13(1): 9 (2020) - [j133]Jason H. Moore:
Ten important roles for academic leaders in data science. BioData Min. 13(1): 18 (2020) - [j132]Owen Wetherbee, Jessica R. Meeker, Caroline Devoto, Trevor M. Penning, Jason H. Moore, Mary Regina Boland:
WellExplorer: an integrative resource linking hydraulic fracturing chemicals with hormonal pathways and geographic location. Database J. Biol. Databases Curation 2020 (2020) - [j131]Trang T. Le, Weixuan Fu, Jason H. Moore:
Scaling tree-based automated machine learning to biomedical big data with a feature set selector. Bioinform. 36(1): 250-256 (2020) - [j130]Alena Orlenko, Daniel Kofink, Leo-Pekka Lyytikäinen, Kjell Nikus, Pashupati P. Mishra, Pekka Kuukasjärvi, Pekka J. Karhunen, Mika Kähönen, Jari O. Laurikka, Terho Lehtimäki, Folkert W. Asselbergs, Jason H. Moore:
Model selection for metabolomics: predicting diagnosis of coronary artery disease using automated machine learning. Bioinform. 36(6): 1772-1778 (2020) - [j129]Xiaohui Yao, Shan Cong, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Jason H. Moore, Li Shen:
Regional imaging genetic enrichment analysis. Bioinform. 36(8): 2554-2560 (2020) - [j128]Elisabetta Manduchi, Weixuan Fu, Joseph D. Romano, Stefano Ruberto, Jason H. Moore:
Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses. BMC Bioinform. 21(1): 430 (2020) - [j127]Moshe Sipper, Jason H. Moore:
Genetic programming theory and practice: a fifteen-year trajectory. Genet. Program. Evolvable Mach. 21(1-2): 169-179 (2020) - [j126]William G. La Cava, Jason H. Moore:
Learning feature spaces for regression with genetic programming. Genet. Program. Evolvable Mach. 21(3): 433-467 (2020) - [j125]Lingjiao Zhang, Xiruo Ding, Yanyuan Ma, Naveen Muthu, Imran Ajmal, Jason H. Moore, Daniel S. Herman, Jinbo Chen:
A maximum likelihood approach to electronic health record phenotyping using positive and unlabeled patients. J. Am. Medical Informatics Assoc. 27(1): 119-126 (2020) - [j124]Jiayi Tong, Jing Huang, Jessica Chubak, Xuan Wang, Jason H. Moore, Rebecca A. Hubbard, Yong Chen:
An augmented estimation procedure for EHR-based association studies accounting for differential misclassification. J. Am. Medical Informatics Assoc. 27(2): 244-253 (2020) - [j123]Rui Duan, Mary Regina Boland, Zixuan Liu, Yue Liu, Howard H. Chang, Hua Xu, Haitao Chu, Christopher H. Schmid, Christopher B. Forrest, John H. Holmes, Martijn J. Schuemie, Jesse A. Berlin, Jason H. Moore, Yong Chen:
Learning from electronic health records across multiple sites: A communication-efficient and privacy-preserving distributed algorithm. J. Am. Medical Informatics Assoc. 27(3): 376-385 (2020) - [j122]Rui Duan, Chongliang Luo, Martijn J. Schuemie, Jiayi Tong, C. Jason Liang, Howard H. Chang, Mary Regina Boland, Jiang Bian, Hua Xu, John H. Holmes, Christopher B. Forrest, Sally C. Morton, Jesse A. Berlin, Jason H. Moore, Kevin B. Mahoney, Yong Chen:
Learning from local to global: An efficient distributed algorithm for modeling time-to-event data. J. Am. Medical Informatics Assoc. 27(7): 1028-1036 (2020) - [j121]Gabriel A. Brat, Griffin M. Weber, Nils Gehlenborg, Paul Avillach, Nathan P. Palmer, Luca Chiovato, James J. Cimino, Lemuel R. Waitman, Gilbert S. Omenn, Alberto Malovini, Jason H. Moore, Brett K. Beaulieu-Jones, Valentina Tibollo, Shawn N. Murphy, Sehi L'Yi, Mark S. Keller, Riccardo Bellazzi, David A. Hanauer, Arnaud Serret-Larmande, Alba Gutiérrez-Sacristán, John J. Holmes, Douglas S. Bell, Kenneth D. Mandl, Robert W. Follett, Jeffrey G. Klann, Douglas A. Murad, Luigia Scudeller, Mauro Bucalo, Katie G. Kirchoff, Jean B. Craig, Jihad S. Obeid, Vianney Jouhet, Romain Griffier, Sébastien Cossin, Bertrand Moal, Lav P. Patel, Antonio Bellasi, Hans-Ulrich Prokosch, Detlef Kraska, Piotr Sliz, Amelia L. M. Tan, Kee Yuan Ngiam, Alberto Zambelli, Danielle L. Mowery, Emily Schriver, Batsal Devkota, Robert L. Bradford, Mohamad Daniar, Christel Daniel, Vincent Benoit, Romain Bey, Nicolas Paris, Patricia Serre, Nina Orlova, Julien Dubiel, Martin Hilka, Anne-Sophie Jannot, Stéphane Bréant, Judith Leblanc, Nicolas Griffon, Anita Burgun, Mélodie Bernaux, Arnaud Sandrin, Elisa Salamanca, Sylvie Cormont, Thomas Ganslandt, Tobias Gradinger, Julien Champ, Martin Boeker, Patricia Martel, Loic Esteve, Alexandre Gramfort, Olivier Grisel, Damien Leprovost, Thomas Moreau, Gaël Varoquaux, Jill-Jênn Vie, Demian Wassermann, Arthur Mensch, Charlotte Caucheteux, Christian Haverkamp, Guillaume Lemaitre, Silvano Bosari, Ian D. Krantz, Andrew M. South, Tianxi Cai, Isaac S. Kohane:
International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium. npj Digit. Medicine 3 (2020) - [j120]Joseph D. Romano, Jason H. Moore:
Ten simple rules for writing a paper about scientific software. PLoS Comput. Biol. 16(11) (2020) - [j119]Moshe Sipper, Jason H. Moore:
Gamorithm. IEEE Trans. Games 12(1): 115-118 (2020) - [c161]Mary Regina Boland, Lena M. Davidson, Silvia P. Canelón, Jessica R. Meeker, Trevor M. Penning, John H. Holmes, Jason H. Moore:
Harnessing Electronic Health Records to Study Emerging Environmental Disasters: A Proof of Concept with PFAS. AMIA 2020 - [c160]John H. Holmes, Riccardo Bellazzi, Carlo Combi, Jason H. Moore, Niels Peek:
Explainable Artificial Intelligence (XAI): Current Approaches and Paths to the Future. AMIA 2020 - [c159]Nadia M. Penrod, Selah F. Lynch, Jason H. Moore:
Extracting Behavioral Determinants of Health from Electronic Health Records: Classifying Yoga Mentions in the Clinic. HEALTHINF 2020: 77-82 - [c158]Trang T. Le, Hoyt Gong, Patryk Orzechowski, Elisabetta Manduchi, Jason H. Moore:
Expanding Polygenic Risk Scores to Include Automatic Genotype Encodings and Gene-gene Interactions. BIOINFORMATICS 2020: 79-84 - [c157]Ruowang Li, Jiayi Tong, Rui Duan, Yong Chen, Jason H. Moore:
Evaluation of Phenotyping Errors on Polygenic Risk Score Predictions. BIOINFORMATICS 2020: 123-130 - [c156]Patryk Orzechowski, Franciszek Magiera, Jason H. Moore:
Benchmarking Manifold Learning Methods on a Large Collection of Datasets. EuroGP 2020: 135-150 - [c155]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
SGP-DT: Semantic Genetic Programming Based on Dynamic Targets. EuroGP 2020: 167-183 - [c154]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Coevolving Artistic Images Using OMNIREP. EvoMUSART 2020: 165-178 - [c153]Trang T. Le, Weixuan Fu, Jason H. Moore:
Large scale biomedical data analysis with tree-based automated machine learning. GECCO Companion 2020: 21-22 - [c152]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
SGP-DT: towards effective symbolic regression with a semantic GP approach based on dynamic targets. GECCO Companion 2020: 25-26 - [c151]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
Image feature learning with a genetic programming autoencoder. GECCO Companion 2020: 245-246 - [c150]