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ORCIDPing Zhang 0016
Person information
- affiliation: Ohio State University, Columbus, OH, USA
- affiliation: IBM Thomas J. Watson Research Center, Center for Computational Health, Yorktown Heights, NY, USA
- affiliation (PhD 2012): Temple University, Center for Data Analytics and Biomedical Informatics, Philadelphia, PA, USA
Other persons with the same name
- Ping Zhang — disambiguation page
- Ping Zhang 0001 — University of California at San Diego, San Diego, CA, USA
- Ping Zhang 0002
![[0000-0003-0663-1850]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0003-0663-1850")
— Syracuse University, Syracuse, NY, USA - Ping Zhang 0003 — Beijing University of Posts and Telecommunications, State Key Laboratory of Networking and Switching Technology, China (and 2 more)
- Ping Zhang 0004 — Western Michigan University, Kalamazoo, MI, USA
- Ping Zhang 0005 — Alcorn State University, USA
- Ping Zhang 0006 — Tianjin University, School of Civil Engineering, China
- Ping Zhang 0008 — Bond University, Faculty of Health Sciences and Medicine, Robina, QLD, Australia
- Ping Zhang 0009 — Peking University, Key Laboratory of Machine Perception, Beijing, China
- Ping Zhang 0010 — Department of Biomedical Engineering, Indiana University
- Ping Zhang 0011 — Hydrospheric & Biospheric Sci. Lab., NASA's Goddard Space Flight Center, Greenbelt, MD, USA
- Ping Zhang 0013 — Avaya Labs Research, Basking Ridge, NJ, USA
- Ping Zhang 0014 — Department of Manufacturing Engineering, Boston University, Boston, MA, USA
- Ping Zhang 0015 — South China University of Science and Technology, School of Computer Science and Engineering, Guangzhou, China (and 1 more)
- Ping Zhang 0017 — Department of Computer and Information Science, Indiana University Purdue University, Indianapolis, IN, USA
- Ping Zhang 0018 — Tsinghua University, Department of Engineering Physics, Institute of Public Safety Research, Beijing, China
- Ping Zhang 0019 — China Agricultural University, College of Natural Resources and Environmental Sciences, Beijing, China
- Ping Zhang 0020 — University of Science and Technology of China, Key Laboratory of Electromagnetic Space Information, Hefei, China
- Ping Zhang 0021 — Chongqing University, Journals Department, China
- Ping Zhang 0022 — University of Kaiserslautern, Institute of Automatic Control, Germany (and 1 more)
- Ping Zhang 0023 — University of Electronic Science and Technology of China, School of Optoelectronic Science and Engineering, Chengdu, China
- Ping Zhang 0024 — Chinese Academy of Sciences, Key Laboratory of Digital Earth Science, Beijing, China
- Ping Zhang 0025 — Hebei University of Technology, School of Artificial Intelligence, Hebei Province Key Laboratory of Big Data Calculation, Tianjin, China (and 2 more)
- Ping Zhang 0026 — State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, China
- Ping Zhang 0027 — Huazhong Agricultural University, College of Informatics, Wuhan, China (and 1 more)
- Ping Zhang 0028 — Henan University of Science and Technology, School of Mathematics and Statistics, Luoyang, China
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2020 – today
- 2024
[j28]Jiajia Li, Pingping Zhang, Xia Yang, Lei Zhu, Teng Wang, Ping Zhang, Ruhan Liu, Bin Sheng, Kaixuan Wang:
SSM-Net: Semi-supervised multi-task network for joint lesion segmentation and classification from pancreatic EUS images. Artif. Intell. Medicine 154: 102919 (2024)- [j27]Ruhan Liu, Jiajia Li, Yang Wen, Huating Li, Ping Zhang, Bin Sheng, David Dagan Feng:
DDE: Deep Dynamic Epidemiological Modeling for Infectious Illness Development Forecasting in Multi-level Geographic Entities. J. Heal. Informatics Res. 8(3): 478-505 (2024) - [j26]Ruoqi Liu, Pin-Yu Chen, Ping Zhang:
CURE: A deep learning framework pre-trained on large-scale patient data for treatment effect estimation. Patterns 5(6): 100973 (2024) - [c57]Ruoqi Liu, Lingfei Wu, Ping Zhang:
KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing Patient Data with Knowledge Graphs. AAAI 2024: 8805-8814 - [c56]Shao Zhang, Jianing Yu, Xuhai Xu, Changchang Yin, Yuxuan Lu, Bingsheng Yao, Melanie Tory, Lace M. K. Padilla, Jeffrey M. Caterino, Ping Zhang, Dakuo Wang:
Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis. CHI 2024: 445:1-445:18 - [c55]Jiayuan Chen, Changchang Yin, Yuanlong Wang, Ping Zhang:
Predictive Modeling with Temporal Graphical Representation on Electronic Health Records. IJCAI 2024: 5763-5771 - [c54]Changchang Yin, Pin-Yu Chen, Bingsheng Yao, Dakuo Wang, Jeffrey M. Caterino, Ping Zhang:
SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing. KDD 2024: 6158-6168 - [i28]Seungyeon Lee, Ruoqi Liu, Wenyu Song, Lang Li, Ping Zhang:
SubgroupTE: Advancing Treatment Effect Estimation with Subgroup Identification. CoRR abs/2401.12369 (2024) - [i27]Seungyeon Lee, Ruoqi Liu, Wenyu Song, Ping Zhang:
Heterogeneous treatment effect estimation with subpopulation identification for personalized medicine in opioid use disorder. CoRR abs/2401.17027 (2024) - [i26]Ruoqi Liu, Lingfei Wu, Ping Zhang:
KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing Patient Data with Knowledge Graphs. CoRR abs/2403.03791 (2024) - [i25]Jiayuan Chen, Changchang Yin, Yuanlong Wang, Ping Zhang:
Predictive Modeling with Temporal Graphical Representation on Electronic Health Records. CoRR abs/2405.03943 (2024) - [i24]Thai-Hoang Pham, Xueru Zhang, Ping Zhang:
Non-stationary Domain Generalization: Theory and Algorithm. CoRR abs/2405.06816 (2024) - [i23]Zishan Gu, Fenglin Liu, Changchang Yin, Ping Zhang:
Inquire, Interact, and Integrate: A Proactive Agent Collaborative Framework for Zero-Shot Multimodal Medical Reasoning. CoRR abs/2405.11640 (2024) - [i22]Zishan Gu, Changchang Yin, Fenglin Liu, Ping Zhang:
MedVH: Towards Systematic Evaluation of Hallucination for Large Vision Language Models in the Medical Context. CoRR abs/2407.02730 (2024) - [i21]Changchang Yin, Pin-Yu Chen, Bingsheng Yao, Dakuo Wang, Jeffrey M. Caterino, Ping Zhang:
SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing. CoRR abs/2407.16999 (2024) - [i20]Siyi Wu, Weidan Cao, Shihan Fu, Bingsheng Yao, Ziqi Yang, Changchang Yin, Varun Mishra, Daniel Addison, Ping Zhang, Dakuo Wang:
Clinical Challenges and AI Opportunities in Decision-Making for Cancer Treatment-Induced Cardiotoxicity. CoRR abs/2408.03586 (2024) - [i19]Zheda Mai, Arpita Chowdhury, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Vardaan Pahuja, Tanya Y. Berger-Wolf, Song Gao, Charles V. Stewart, Yu Su, Wei-Lun Chao:
Fine-Tuning is Fine, if Calibrated. CoRR abs/2409.16223 (2024) - [i18]Zheda Mai, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Li Zhang, Wei-Lun Chao:
Lessons Learned from a Unifying Empirical Study of Parameter-Efficient Transfer Learning (PETL) in Visual Recognition. CoRR abs/2409.16434 (2024) - [i17]Siyi Wu, Weidan Cao, Shihan Fu, Bingsheng Yao, Ziqi Yang, Changchang Yin, Varun Mishra, Daniel Addison, Ping Zhang, Dakuo Wang:
CardioAI: A Multimodal AI-based System to Support Symptom Monitoring and Risk Detection of Cancer Treatment-Induced Cardiotoxicity. CoRR abs/2410.04592 (2024) - 2023
- [j25]Liuping Wang, Zhan Zhang, Dakuo Wang, Weidan Cao, Xiaomu Zhou, Ping Zhang, Jianxing Liu, Xiangmin Fan, Feng Tian:
Human-centered design and evaluation of AI-empowered clinical decision support systems: a systematic review. Frontiers Comput. Sci. 5 (2023) - [j24]Thai-Hoang Pham, Changchang Yin, Laxmi Mehta, Xueru Zhang, Ping Zhang:
A fair and interpretable network for clinical risk prediction: a regularized multi-view multi-task learning approach. Knowl. Inf. Syst. 65(4): 1487-1521 (2023) - [j23]Ruoqi Liu, Katherine M. Hunold, Jeffrey M. Caterino, Ping Zhang:
Estimating treatment effects for time-to-treatment antibiotic stewardship in sepsis. Nat. Mac. Intell. 5(4): 421-431 (2023) - [j22]Seungyeon Lee, Changchang Yin, Ping Zhang:
Stable clinical risk prediction against distribution shift in electronic health records. Patterns 4(9): 100828 (2023) - [j21]Ruhan Liu, Tianqin Wang, Huating Li, Ping Zhang, Jing Li, Xiaokang Yang, Dinggang Shen, Bin Sheng:
TMM-Nets: Transferred Multi- to Mono-Modal Generation for Lupus Retinopathy Diagnosis. IEEE Trans. Medical Imaging 42(4): 1083-1094 (2023) - [c53]Seungyeon Lee, Ruoqi Liu, Wenyu Song, Ping Zhang:
Heterogeneous Treatment Effect Estimation with Subpopulation Identification for Personalized Medicine in Opioid Use Disorder. ICDM 2023: 1079-1084 - [c52]Thai-Hoang Pham, Xueru Zhang, Ping Zhang:
Fairness and Accuracy under Domain Generalization. ICLR 2023 - [i16]Thai-Hoang Pham, Xueru Zhang, Ping Zhang:
Fairness and Accuracy under Domain Generalization. CoRR abs/2301.13323 (2023) - [i15]Bo Qian, Hao Chen, Xiangning Wang, Haoxuan Che, Gitaek Kwon, Jaeyoung Kim, Sungjin Choi, Seoyoung Shin, Felix Krause, Markus Unterdechler, Junlin Hou, Rui Feng, Yihao Li, Mostafa El Habib Daho, Qiang Wu, Ping Zhang, Xiaokang Yang, Yiyu Cai, Weiping Jia, Huating Li, Bin Sheng:
DRAC: Diabetic Retinopathy Analysis Challenge with Ultra-Wide Optical Coherence Tomography Angiography Images. CoRR abs/2304.02389 (2023) - [i14]Ruhan Liu, Jiajia Li, Yang Wen, Huating Li, Ping Zhang, Bin Sheng, David Dagan Feng:
Deep Dynamic Epidemiological Modelling for COVID-19 Forecasting in Multi-level Districts. CoRR abs/2306.12457 (2023) - [i13]Shao Zhang, Jianing Yu, Xuhai Xu, Changchang Yin, Yuxuan Lu, Bingsheng Yao, Melanie Tory, Lace M. K. Padilla, Jeffrey M. Caterino, Ping Zhang, Dakuo Wang:
Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis. CoRR abs/2309.12368 (2023) - [i12]Seungyeon Lee, Thai-Hoang Pham, Zhao Cheng, Ping Zhang:
Domain Invariant Representation Learning and Sleep Dynamics Modeling for Automatic Sleep Staging. CoRR abs/2312.03196 (2023) - 2022
- [j20]Thai-Hoang Pham, Yue Qiu, Jiahui Liu, Steven Zimmer, Eric E. O'Neill, Lei Xie, Ping Zhang:
Chemical-induced gene expression ranking and its application to pancreatic cancer drug repurposing. Patterns 3(4): 100441 (2022) - [j19]Ruhan Liu, Xiangning Wang, Qiang Wu, Ling Dai, Xi Fang, Tao Yan, Jaemin Son, Shiqi Tang, Jiang Li, Zijian Gao, Adrian Galdran, J. M. Poorneshwaran, Hao Liu, Jie Wang, Yerui Chen, Prasanna Porwal, Gavin Siew Wei Tan, Xiaokang Yang, Chao Dai, Haitao Song, Mingang Chen, Huating Li, Weiping Jia, Dinggang Shen, Bin Sheng, Ping Zhang:
DeepDRiD: Diabetic Retinopathy - Grading and Image Quality Estimation Challenge. Patterns 3(6): 100512 (2022) - [j18]Ruhan Liu, Liang Ou, Bin Sheng, Pei Hao, Ping Li, Xiaokang Yang, Guangtao Xue, Lei Zhu, Yuyang Luo, Ping Zhang, Po Yang, Huating Li, David Dagan Feng:
Mixed-Weight Neural Bagging for Detecting $m^6A$ Modifications in SARS-CoV-2 RNA Sequencing. IEEE Trans. Biomed. Eng. 69(8): 2557-2568 (2022) - [c51]Seungyeon Lee, Thai-Hoang Pham, Ping Zhang:
DREAM: Domain Invariant and Contrastive Representation for Sleep Dynamics. ICDM 2022: 1029-1034 - [c50]Changchang Yin, Ruoqi Liu, Jeffrey M. Caterino, Ping Zhang:
Deconfounding Actor-Critic Network with Policy Adaptation for Dynamic Treatment Regimes. KDD 2022: 2316-2326 - [c49]Changchang Yin, Sayoko E. Moroi, Ping Zhang:
Predicting Age-Related Macular Degeneration Progression with Contrastive Attention and Time-Aware LSTM. KDD 2022: 4402-4412 - [c48]Thai-Hoang Pham, Lei Xie, Ping Zhang:
FAME: Fragment-based Conditional Molecular Generation for Phenotypic Drug Discovery. SDM 2022: 720-728 - [i11]Changchang Yin, Ruoqi Liu, Jeffrey M. Caterino, Ping Zhang:
Deconfounding Actor-Critic Network with Policy Adaptation for Dynamic Treatment Regimes. CoRR abs/2205.09852 (2022) - 2021
- [j17]Qianlong Wen, Ruoqi Liu, Ping Zhang:
Clinical connectivity map for drug repurposing: using laboratory results to bridge drugs and diseases. BMC Medical Informatics Decis. Mak. 21(8): 263 (2021) - [j16]Ruoqi Liu, Lai Wei, Ping Zhang:
A deep learning framework for drug repurposing via emulating clinical trials on real-world patient data. Nat. Mach. Intell. 3(1): 68-75 (2021) - [j15]Thai-Hoang Pham, Yue Qiu, Jucheng Zeng, Lei Xie, Ping Zhang:
A deep learning framework for high-throughput mechanism-driven phenotype compound screening and its application to COVID-19 drug repurposing. Nat. Mach. Intell. 3(3): 247-257 (2021) - [j14]Yuanfang Guan, Hongyang Li, Daiyao Yi, Dongdong Zhang, Changchang Yin, Keyu Li, Ping Zhang:
A survival model generalized to regression learning algorithms. Nat. Comput. Sci. 1(6): 433-440 (2021) - [j13]Dongdong Zhang, Changchang Yin, Katherine M. Hunold, Xiaoqian Jiang, Jeffrey M. Caterino, Ping Zhang:
An interpretable deep-learning model for early prediction of sepsis in the emergency department. Patterns 2(2): 100196 (2021) - [j12]Ruhan Liu, Mengyao Liu, Bin Sheng, Huating Li, Ping Li, Haitao Song, Ping Zhang, Lixin Jiang, Dinggang Shen:
NHBS-Net: A Feature Fusion Attention Network for Ultrasound Neonatal Hip Bone Segmentation. IEEE Trans. Medical Imaging 40(12): 3446-3458 (2021) - [c47]Fenglin Liu, Changchang Yin, Xian Wu, Shen Ge, Ping Zhang, Xu Sun:
Contrastive Attention for Automatic Chest X-ray Report Generation. ACL/IJCNLP (Findings) 2021: 269-280 - [c46]Biplob Biswas, Thai-Hoang Pham, Ping Zhang:
TransICD: Transformer Based Code-Wise Attention Model for Explainable ICD Coding. AIME 2021: 469-478 - [c45]Thai-Hoang Pham, Changchang Yin, Laxmi Mehta, Xueru Zhang, Ping Zhang:
Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning. ICDM 2021: 499-508 - [c44]Zicong Zhang, Changchang Yin, Ping Zhang:
Temporal Clustering with External Memory Network for Disease Progression Modeling. ICDM 2021: 956-965 - [i10]Biplob Biswas, Thai-Hoang Pham, Ping Zhang:
TransICD: Transformer Based Code-wise Attention Model for Explainable ICD Coding. CoRR abs/2104.10652 (2021) - [i9]Fenglin Liu, Changchang Yin, Xian Wu, Shen Ge, Ping Zhang, Xu Sun:
Contrastive Attention for Automatic Chest X-ray Report Generation. CoRR abs/2106.06965 (2021) - [i8]Thai-Hoang Pham, Changchang Yin, Laxmi Mehta, Xueru Zhang, Ping Zhang:
Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning. CoRR abs/2109.12276 (2021) - [i7]Zicong Zhang, Changchang Yin, Ping Zhang:
Temporal Clustering with External Memory Network for Disease Progression Modeling. CoRR abs/2109.14147 (2021) - 2020
- [j11]Xiang Yue, Zhen Wang, Jingong Huang, Srinivasan Parthasarathy, Soheil Moosavinasab, Yungui Huang, Simon M. Lin, Wen Zhang, Ping Zhang, Huan Sun:
Graph embedding on biomedical networks: methods, applications and evaluations. Bioinform. 36(4): 1241-1251 (2020) - [j10]Dongdong Zhang, Changchang Yin, Jucheng Zeng, Xiaohui Yuan, Ping Zhang:
Combining structured and unstructured data for predictive models: a deep learning approach. BMC Medical Informatics Decis. Mak. 20(1): 280 (2020) - [j9]Sundreen Asad Kamal, Changchang Yin, Buyue Qian, Ping Zhang:
An interpretable risk prediction model for healthcare with pattern attention. BMC Medical Informatics Decis. Mak. 20-S(11): 307 (2020) - [c43]Sanjoy Dey, Ping Zhang, Mohamed F. Ghalwash, Chandramouli Maduri, Daby Sow, Zachary Shahn:
Finding Causal Mechanistic Drug-Drug Interactions from Observational Data. AMIA 2020 - [c42]Bernal Jimenez Gutierrez, Jucheng Zeng, Dongdong Zhang, Ping Zhang, Yu Su:
Document Classification for COVID-19 Literature. EMNLP (Findings) 2020: 3715-3722 - [c41]Ruoqi Liu, Changchang Yin, Ping Zhang:
Estimating Individual Treatment Effects with Time-Varying Confounders. ICDM 2020: 382-391 - [c40]Changchang Yin, Ruoqi Liu, Dongdong Zhang, Ping Zhang:
Identifying Sepsis Subphenotypes via Time-Aware Multi-Modal Auto-Encoder. KDD 2020: 862-872 - [i6]Bernal Jiménez Gutiérrez, Juncheng Zeng, Dongdong Zhang, Ping Zhang, Yu Su:
Document Classification for COVID-19 Literature. CoRR abs/2006.13816 (2020) - [i5]Bortik Bandyopadhyay, Pranav Maneriker, Vedang Patel, Saumya Yashmohini Sahai, Ping Zhang, Srinivasan Parthasarathy:
DrugDBEmbed : Semantic Queries on Relational Database using Supervised Column Encodings. CoRR abs/2007.02384 (2020) - [i4]Ruoqi Liu, Lai Wei, Ping Zhang:
When deep learning meets causal inference: a computational framework for drug repurposing from real-world data. CoRR abs/2007.10152 (2020) - [i3]Zicong Zhang, Kimerly A. Powell, Changchang Yin, Shilei Cao, Dani Gonzalez, Yousef Hannawi, Ping Zhang:
Brain Atlas Guided Attention U-Net for White Matter Hyperintensity Segmentation. CoRR abs/2010.09586 (2020) - [i2]Dongdong Zhang, Xiaohui Yuan, Ping Zhang:
Interpretable Deep Learning for Automatic Diagnosis of 12-lead Electrocardiogram. CoRR abs/2010.10328 (2020)
2010 – 2019
- 2019
- [j8]Ruoqi Liu, Ping Zhang:
Towards early detection of adverse drug reactions: combining pre-clinical drug structures and post-market safety reports. BMC Medical Informatics Decis. Mak. 19(1): 279 (2019) - [c39]Gaocai Dong, Ping Zhang, Jingya Yang, Dongdong Zhang, Jing Peng:
A Systematic Framework for Drug Repurposing based on Literature Mining. BIBM 2019: 939-942 - [c38]Changchang Yin, Rongjian Zhao, Buyue Qian, Xin Lv, Ping Zhang:
Domain Knowledge Guided Deep Learning with Electronic Health Records. ICDM 2019: 738-747 - [c37]Sanjoy Dey, Ping Zhang, Daby Sow, Kenney Ng:
PerDREP: Personalized Drug Effectiveness Prediction from Longitudinal Observational Data. KDD 2019: 1258-1268 - [i1]Xiang Yue, Zhen Wang, Jingong Huang, Srinivasan Parthasarathy, Soheil Moosavinasab, Yungui Huang, Simon M. Lin, Wen Zhang, Ping Zhang, Huan Sun:
Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations. CoRR abs/1906.05017 (2019) - 2018
- [j7]Sanjoy Dey, Heng Luo, Achille Fokoue, Jianying Hu, Ping Zhang:
Predicting adverse drug reactions through interpretable deep learning framework. BMC Bioinform. 19-S(21): 476:1-476:13 (2018) - [j6]J. Shim, Heng Luo, Ping Zhang, Ying Li:
Systematic analysis of drug combinations that mitigate adverse drug reactions. IBM J. Res. Dev. 62(6): 7:1-7:9 (2018) - [c36]Sanjoy Dey, Ping Zhang, Mohamed F. Ghalwash, Zach Shahn, Daby Sow:
Estimating Causal Multi-Drug-Drug Interaction for Adverse Drug Reactions. AMIA 2018 - [c35]Sanjoy Dey, Ping Zhang, Kenney Ng:
Estimating Personalized Drug Effects with Longitudinal Observational Data. AMIA 2018 - [c34]Kyle Yingkai Gao, Achille Fokoue, Heng Luo, Sanjoy Dey, Arun Iyengar, Ping Zhang:
An Interpretable End-to-End Framework for Drug-Target Interaction Prediction Through Deep Neural Representation. AMIA 2018 - [c33]Arun Iyengar, Ashish Kundu, Upendra Sharma, Ping Zhang:
A Trusted Healthcare Data Analytics Cloud Platform. ICDCS 2018: 1238-1249 - [c32]Kyle Yingkai Gao, Achille Fokoue, Heng Luo, Arun Iyengar, Sanjoy Dey, Ping Zhang:
Interpretable Drug Target Prediction Using Deep Neural Representation. IJCAI 2018: 3371-3377 - [c31]Rachel Hodos, Ping Zhang, Hao-Chih Lee, Qiaonan Duan, Zichen Wang, Neil R. Clark, Avi Ma'ayan, Fei Wang, Brian A. Kidd, Jianying Hu, David A. Sontag, Joel Dudley:
Cell-specific prediction and application of drug-induced gene expression . PSB 2018: 32-43 - 2017
- [j5]Ibrahim Abdelaziz, Achille Fokoue, Oktie Hassanzadeh, Ping Zhang, Mohammad Sadoghi:
Large-scale structural and textual similarity-based mining of knowledge graph to predict drug-drug interactions. J. Web Semant. 44: 104-117 (2017) - [c30]Bo Jin, Haoyu Yang, Cao Xiao, Ping Zhang, Xiaopeng Wei, Fei Wang:
Multitask Dyadic Prediction and Its Application in Prediction of Adverse Drug-Drug Interaction. AAAI 2017: 1367-1373 - [c29]Cao Xiao, Ping Zhang, W. Art Chaovalitwongse, Jianying Hu, Fei Wang:
Adverse Drug Reaction Prediction with Symbolic Latent Dirichlet Allocation. AAAI 2017: 1590-1596 - [c28]Janu Verma, Heng Luo, Jianying Hu, Ping Zhang:
DrugPathSeeker: Interactive UI for exploring drug-ADR relation via pathways. PacificVis 2017: 260-264 - [c27]Mohamed F. Ghalwash, Ying Li, Ping Zhang, Jianying Hu:
Exploiting Electronic Health Records to Mine Drug Effects on Laboratory Test Results. CIKM 2017: 1837-1846 - [c26]Shijing Guo, Xiang Li, Haifeng Liu, Ping Zhang, Xin Du, Guotong Xie, Fei Wang:
Integrating Temporal Pattern Mining in Ischemic Stroke Prediction and Treatment Pathway Discovery for Atrial Fibrillation. CRI 2017 - [c25]Kun Lin, Ping Zhang, Gigi Y. Yuen-Reed, Ying Li, Jianying Hu:
Improving predictive models with clustered sequences: An Application on Heart Failure Risk Prediction. CRI 2017 - [c24]Haifeng Liu, Xiang Li, Guotong Xie, Xin Du, Ping Zhang, Chengming Gu, Jingyi Hu:
Precision Cohort Finding with Outcome-Driven Similarity Analytics: A Case Study of Patients with Atrial Fibrillation. MedInfo 2017: 491-495 - [c23]Yashu Liu, Shuang Qiu, Ping Zhang, Pinghua Gong, Fei Wang, Guoliang Xue, Jieping Ye:
Computational Drug Discovery with Dyadic Positive-Unlabeled Learning. SDM 2017: 45-53 - [c22]Ioakeim Perros, Fei Wang, Ping Zhang, Peter B. Walker, Richard W. Vuduc, Jyotishman Pathak, Jimeng Sun:
Polyadic Regression and its Application to Chemogenomics. SDM 2017: 72-80 - 2016
- [c21]Achille Fokoue, Oktie Hassanzadeh, Mohammad Sadoghi, Ping Zhang:
Tiresias: Knowledge Engineering and Large-Scale Machine Learning for Interpretable Drug-Drug Interaction Prediction. AMIA 2016 - [c20]Achille Fokoue, Ping Zhang, Oktie Hassanzadeh, Mohammad Sadoghi:
Towards Large-Scale Predictive Drug Safety: A Computational Framework for Inferring Drug Interactions Through Similarity-Based Link Prediction. AMIA 2016 - [c19]Xiang Li, Haifeng Liu, Xin Du, Ping Zhang, Gang Hu, Guo Tong Xie, Shijing Guo, Meilin Xu, Xiaoping Xie:
Integrated Machine Learning Approaches for Predicting Ischemic Stroke and Thromboembolism in Atrial Fibrillation. AMIA 2016 - [c18]Ying Li, Ping Zhang, Zhaonan Sun, Jianying Hu:
Data-Driven Prediction of Beneficial Drug Combinations in Spontaneous Reporting Systems. AMIA 2016 - [c17]Zhaonan Sun, Xu Liu, Ping Zhang, Jianying Hu, Juan Wisnivesky:
Joint Modeling of Survival Events through Multi-task Learning Framework. AMIA 2016 - [c16]Achille Fokoue, Mohammad Sadoghi, Oktie Hassanzadeh, Ping Zhang:
Predicting Drug-Drug Interactions Through Large-Scale Similarity-Based Link Prediction. ESWC 2016: 774-789 - [c15]Fei Wang, Ping Zhang, Joel Dudley:
Healthcare Data Mining with Matrix Models. KDD 2016: 2137-2138 - [c14]Xiang Li, Haifeng Liu, Xin Du, Gang Hu, Guotong Xie, Ping Zhang:
Using Frequent Item Set Mining and Feature Selection Methods to Identify Interacted Risk Factors - The Atrial Fibrillation Case Study. MIE 2016: 562-566 - [c13]Yu Cheng, Fei Wang, Ping Zhang, Jianying Hu:
Risk Prediction with Electronic Health Records: A Deep Learning Approach. SDM 2016: 432-440 - [c12]Achille Fokoue, Oktie Hassanzadeh, Mohammad Sadoghi, Ping Zhang:
Predicting Drug-Drug Interactions Through Similarity-Based Link Prediction Over Web Data. WWW (Companion Volume) 2016: 175-178 - 2015
- [c11]Ping Zhang, Zhaonan Sun, Fei Wang, Jianying Hu:
Towards Computational Drug Repositioning: A Comparative Study of Single-task and Multi-task Learning. AMIA 2015 - [c10]Kenney Ng, Chris Kakkanatt, Michael Benigno, Clay Thompson, Margaret Jackson, Amos Cahan, Xinxin Zhu, Ping Zhang, Paul Huang:
Curating and Integrating Data from Multiple Sources to Support Healthcare Analytics. MedInfo 2015: 1056 - 2014
- [j4]Jimeng Sun, Candace D. McNaughton, Ping Zhang, Adam Perer, Aris Gkoulalas-Divanis, Joshua C. Denny, Jacqueline Kirby, Thomas A. Lasko, Alexander Saip, Bradley A. Malin:
Predicting changes in hypertension control using electronic health records from a chronic disease management program. J. Am. Medical Informatics Assoc. 21(2): 337-344 (2014) - [j3]Fei Wang, Ping Zhang, Nan Cao, Jianying Hu, Robert Sorrentino:
Exploring the associations between drug side-effects and therapeutic indications. J. Biomed. Informatics 51: 15-23 (2014) - [j2]Heng Luo, Ping Zhang, Hui Huang, Jialiang Huang, Emily Kao, Leming Shi, Lin He, Lun Yang:
DDI-CPI, a server that predicts drug-drug interactions through implementing the chemical-protein interactome. Nucleic Acids Res. 42(Webserver-Issue): 46-52 (2014) - [c9]Fei Wang, Ping Zhang, Xiang Wang, Jianying Hu:
Clinical Risk Prediction by Exploring High-Order Feature Correlations. AMIA 2014 - [c8]Ping Zhang, Fei Wang, Jianying Hu:
Towards Drug Repositioning: A Unified Computational Framework for Integrating Multiple Aspects of Drug Similarity and Disease Similarity. AMIA 2014 - [c7]Fei Wang, Ping Zhang, Buyue Qian, Xiang Wang, Ian Davidson:
Clinical risk prediction with multilinear sparse logistic regression. KDD 2014: 145-154 - 2013
- [j1]Ping Zhang, Weidan Cao, Zoran Obradovic:
Learning by aggregating experts and filtering novices: a solution to crowdsourcing problems in bioinformatics. BMC Bioinform. 14(S-12): S5 (2013) - [c6]Ping Zhang, Fei Wang, Jianying Hu, Robert Sorrentino:
Exploring the Relationship Between Drug Side-Effects and Therapeutic Indications. AMIA 2013 - [c5]Ping Zhang, Pankaj Agarwal, Zoran Obradovic:
Computational Drug Repositioning by Ranking and Integrating Multiple Data Sources. ECML/PKDD (3) 2013: 579-594 - 2012
- [c4]Ping Zhang, Zoran Obradovic:
Integration of multiple annotators by aggregating experts and filtering novices. BIBM 2012: 1-6 - [c3]Jelena Slivka, Ping Zhang, Aleksandar Kovacevic, Zora Konjovic, Zoran Obradovic:
Semi-Supervised Learning on Single-View Datasets by Integration of Multiple Co-trained Classifiers. ICMLA (1) 2012: 458-463 - 2011
- [c2]Ping Zhang, Zoran Obradovic:
Learning from Inconsistent and Unreliable Annotators by a Gaussian Mixture Model and Bayesian Information Criterion. ECML/PKDD (3) 2011: 553-568 - 2010
- [c1]Ping Zhang, Zoran Obradovic:
Unsupervised integration of multiple protein disorder predictors. BIBM 2010: 49-52
Coauthor Index
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