| Risk Prediction with Electronic Health Records: A Deep Learning Approach Y Cheng, F Wang, P Zhang, J Hu SIAM International Conference on Data Mining (SDM16), 2016 | 245 | 2016 |
| Label propagation prediction of drug-drug interactions based on clinical side effects P Zhang, F Wang, J Hu, R Sorrentino Scientific reports 5 (1), 1-10, 2015 | 107 | 2015 |
| Towards Personalized Medicine: Leveraging Patient Similarity and Drug Similarity Analytics P Zhang, F Wang, J Hu, R Sorrentino AMIA Summits Transl Sci Proc, 132-136, 2014 | 88 | 2014 |
| Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations X Yue, Z Wang, J Huang, S Parthasarathy, S Moosavinasab, Y Huang, ... Bioinformatics, btz718, 2020 | 70 | 2020 |
| Interpretable Drug Target Prediction Using Deep Neural Representation KY Gao, A Fokoue, H Luo, A Iyengar, S Dey, P Zhang The 27th International Joint Conference on Artificial Intelligence, 3371-3377, 2018 | 65 | 2018 |
| DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome H Luo, P Zhang, H Huang, J Huang, E Kao, L Shi, L He, L Yang Nucleic acids research 42 (W1), W46-W52, 2014 | 64 | 2014 |
| Predicting changes in hypertension control using electronic health records from a chronic disease management program J Sun, CD McNaughton, P Zhang, A Perer, A Gkoulalas-Divanis, ... Journal of the American Medical Informatics Association 21 (2), 337-344, 2014 | 64 | 2014 |
| Towards drug repositioning: a unified computational framework for integrating multiple aspects of drug similarity and disease similarity P Zhang, F Wang, J Hu AMIA annual symposium proceedings 2014, 1258, 2014 | 63 | 2014 |
| Clinical Risk Prediction with Multilinear Sparse Logistic Regression F Wang, P Zhang, B Qian, X Wang, I Davidson ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2014 | 53 | 2014 |
| Predicting adverse drug reactions through interpretable deep learning framework S Dey, H Luo, A Fokoue, J Hu, P Zhang BMC bioinformatics 19 (21), 1-13, 2018 | 48 | 2018 |
| Exploring the associations between drug side-effects and therapeutic indications F Wang, P Zhang, N Cao, J Hu, R Sorrentino Journal of biomedical informatics 51, 15-23, 2014 | 43 | 2014 |
| Large-scale structural and textual similarity-based mining of knowledge graph to predict drug–drug interactions I Abdelaziz, A Fokoue, O Hassanzadeh, P Zhang, M Sadoghi Journal of Web Semantics 44, 104-117, 2017 | 41 | 2017 |
| Computational drug repositioning by ranking and integrating multiple data sources P Zhang, P Agarwal, Z Obradovic Joint European Conference on Machine Learning and Knowledge Discovery in …, 2013 | 39 | 2013 |
| Predicting drug-drug interactions through large-scale similarity-based link prediction A Fokoue, M Sadoghi, O Hassanzadeh, P Zhang European Semantic Web Conference, 774-789, 2016 | 32 | 2016 |
| Exploring the Relationship Between Drug Side-Effects and Therapeutic Indications P Zhang, F Wang, J Hu, R Sorrentino AMIA Annu Symp Proc, 1568-1577, 2013 | 32 | 2013 |
| Systematic prediction of drug combinations based on clinical side-effects H Huang, P Zhang, XA Qu, P Sanseau, L Yang Scientific reports 4 (1), 1-7, 2014 | 31 | 2014 |
| Multitask dyadic prediction and its application in prediction of adverse drug-drug interaction B Jin, H Yang, C Xiao, P Zhang, X Wei, F Wang Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 26 | 2017 |
| Integrated machine learning approaches for predicting ischemic stroke and thromboembolism in atrial fibrillation X Li, H Liu, X Du, P Zhang, G Hu, G Xie, S Guo, M Xu, X Xie AMIA Annual Symposium Proceedings 2016, 799, 2016 | 26 | 2016 |
| Adverse drug reaction prediction with symbolic latent dirichlet allocation C Xiao, P Zhang, W Chaovalitwongse, J Hu, F Wang Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 22 | 2017 |
| Learning from inconsistent and unreliable annotators by a gaussian mixture model and bayesian information criterion P Zhang, Z Obradovic Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011 | 22 | 2011 |
