| Inferring causal molecular networks: empirical assessment through a community-based effort SM Hill, LM Heiser, T Cokelaer, M Unger, NK Nesser, DE Carlin, Y Zhang, ... Nature methods 13 (4), 310-318, 2016 | 263 | 2016 |
| Data mining: know it all S Chakrabarti, RE Neapolitan, D Pyle, M Refaat, M Schneider, TJ Teorey, ... Morgan Kaufmann, 2008 | 209 | 2008 |
| Artificial intelligence: With an introduction to machine learning RE Neapolitan, X Jiang CRC press, 2018 | 195 | 2018 |
| Learning genetic epistasis using Bayesian network scoring criteria X Jiang, RE Neapolitan, MM Barmada, S Visweswaran BMC bioinformatics 12, 1-12, 2011 | 118 | 2011 |
| Contemporary artificial intelligence RE Neapolitan CRC press, 2012 | 92 | 2012 |
| Using natural language processing and machine learning to identify breast cancer local recurrence Z Zeng, S Espino, A Roy, X Li, SA Khan, SE Clare, X Jiang, R Neapolitan, ... BMC bioinformatics 19, 65-74, 2018 | 90 | 2018 |
| An informatics research agenda to support precision medicine: seven key areas JD Tenenbaum, P Avillach, M Benham-Hutchins, MK Breitenstein, ... Journal of the American Medical Informatics Association 23 (4), 791-795, 2016 | 89 | 2016 |
| Deep learning and machine learning with grid search to predict later occurrence of breast cancer metastasis using clinical data X Jiang, C Xu Journal of clinical medicine 11 (19), 5772, 2022 | 76 | 2022 |
| A clinical decision support system learned from data to personalize treatment recommendations towards preventing breast cancer metastasis X Jiang, A Wells, A Brufsky, R Neapolitan PloS one 14 (3), e0213292, 2019 | 72 | 2019 |
| Identifying genetic interactions in genome‐wide data using Bayesian networks X Jiang, MM Barmada, S Visweswaran Genetic epidemiology 34 (6), 575-581, 2010 | 72 | 2010 |
| A Bayesian spatio-temporal method for disease outbreak detection X Jiang, GF Cooper Journal of the American Medical Informatics Association 17 (4), 462-471, 2010 | 65 | 2010 |
| Probabilistic graphical models for genetics, genomics, and postgenomics C Sinoquet OUP Oxford, 2014 | 52 | 2014 |
| Discovering causal interactions using Bayesian network scoring and information gain Z Zeng, X Jiang, R Neapolitan BMC bioinformatics 17, 1-14, 2016 | 50 | 2016 |
| Probabilistic methods for financial and marketing informatics RE Neapolitan, X Jiang Elsevier, 2010 | 50 | 2010 |
| Bayesian prediction of an epidemic curve X Jiang, G Wallstrom, GF Cooper, MM Wagner Journal of Biomedical Informatics 42 (1), 90-99, 2009 | 44 | 2009 |
| A novel artificial neural network method for biomedical prediction based on matrix pseudo-inversion B Cai, X Jiang Journal of biomedical informatics 48, 114-121, 2014 | 40 | 2014 |
| Systematic discovery of the functional impact of somatic genome alterations in individual tumors through tumor-specific causal inference C Cai, GF Cooper, KN Lu, X Ma, S Xu, Z Zhao, X Chen, Y Xue, AV Lee, ... PLoS computational biology 15 (7), e1007088, 2019 | 39 | 2019 |
| Pan-cancer analysis of TCGA data reveals notable signaling pathways R Neapolitan, CM Horvath, X Jiang BMC cancer 15, 1-12, 2015 | 39 | 2015 |
| A Bayesian method for evaluating and discovering disease loci associations X Jiang, MM Barmada, GF Cooper, MJ Becich PloS one 6 (8), e22075, 2011 | 39 | 2011 |
| A fast algorithm for learning epistatic genomic relationships X Jiang, RE Neapolitan, MM Barmada, S Visweswaran, GF Cooper AMIA annual Symposium proceedings 2010, 341, 2010 | 39 | 2010 |