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ORCIDHao Liu 0054
Person information
- affiliation: Montclair State University, NJ, USA
- affiliation (former): Columbia University, Department of Biomedical Informatics, New York, USA
- affiliation (PhD 2020): New Jersey Institute of Technology, NJ, USA
Other persons with the same name
- Hao Liu — disambiguation page
- Hao Liu 0001
![[0000-0002-0392-0844]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-0392-0844")
— Chinese Academy of Sciences, National Space Science Center, Key Laboratory of Microwave Remote Sensing, Beijing, China - Hao Liu 0002 — Donghua University, College of Information Science and Technology, Shanghai, China
- Hao Liu 0003 — Tencent YouTu Lab, Hefei, China (and 1 more)
- Hao Liu 0004 — Beihang University, School of Astronautics, Beijing, China (and 1 more)
- Hao Liu 0005 — University College London, UK
- Hao Liu 0006 — Tsinghua University, Department of Computer Science and Technology, Key Laboratory of Pervasive Computing, Beijing, China
- Hao Liu 0007 — Stanford University, Department of Computer Science, Stanford, CA, USA (and 2 more)
- Hao Liu 0008 — Chinese Academie of Sciences, Shenyang Institute of Automation, State Key Laboratory of Robotics, China (and 2 more)
- Hao Liu 0009 — Technical University Eindhoven, Netherlands
- Hao Liu 0010 — Pioneer Suntec Electronic Technology Co., Ltd, Shanghai, China (and 1 more)
- Hao Liu 0011 — Hong Kong University of Science and Technology, Department of Computer Science and Engineering, Hong Kong (and 1 more)
- Hao Liu 0012 — Shenyang Aerospace University, Faculty of Aerospace Engineering, China (and 1 more)
- Hao Liu 0013 — Southeast University, National ASIC System Engineering Research Center, Nanjing, Wuxi, China
- Hao Liu 0014 — Alcatel-Lucent, Shanghai, China
- Hao Liu 0015 — Duke University, Durham, NC, USA (and 1 more)
- Hao Liu 0016 — Chiba University, Graduate School of Engineering, Japan
- Hao Liu 0017 — Guangxi University of Technology, Liuzhou, China
- Hao Liu 0018 — Stanford University, CA, USA (and 1 more)
- Hao Liu 0019 — Ningxia University, School of Information Engineering, Yinchuan, China (and 1 more)
- Hao Liu 0020 — University of Warwick, UK
- Hao Liu 0021 — LMA, Marseille, France
- Hao Liu 0022 — LIP6, Paris, France
- Hao Liu 0023 — Zhejiang University, State Key Laboratory of Industrial Control Technology, Hangzhou, China
- Hao Liu 0024 — Central South University, Changsha, China
- Hao Liu 0025 — New Jersey Institute of Technology (NJIT), Newark, NJ, USA
- Hao Liu 0026 — Hong Kong University of Science and Technology-Guangzhou (HKUST-GZ), Guangzhou, China (and 3 more)
- Hao Liu 0027 — Shanghai Jiao Tong University, School of Biomedical Engineering, China
- Hao Liu 0028 — Hong Kong Baptist University, Department of Mathematics, Hong Kong (and 2 more)
- Hao Liu 0029 — Nanjing University of Aeronautics and Astronautics, College of Mechanical and Electronics, China
- Hao Liu 0030 — Tsinghua University, Department of Electrical Engineering, State Key Laboratory of Power System, Beijing, China
- Hao Liu 0031 — University of Electronic Science and Technology of China, National Key Laboratory of Science and Technology on Communications, Chengdu, China
- Hao Liu 0032 — University of Science and Technology Liaoning, School of Science, Anshan, China (and 1 more)
- Hao Liu 0033 — Shantou University, Department of Electronic Engineering, Shantou, China
- Hao Liu 0034 — Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China
- Hao Liu 0035 — University of Nottingham, Faculty of Engineering, Nottingham, UK
- Hao Liu 0036 — University of Electronic Science and Technology of China, Research Institute of Electronic Science and Technology, Chengdu, China
- Hao Liu 0037 — Beihang University, School of Economics and Management, Beijing, China
- Hao Liu 0038 — North China Electric Power University, State Key Lab of Alternate Electric Power System With Renewable Energy Sources, Beijing, China
- Hao Liu 0039 — Tianjin University, School of Electrical and Information Engineering, Tianjin Key Laboratory of Process Measurement and Control, China
- Hao Liu 0040 — Beijing Municipal Commission of Transport, Beijing Transportation Information Center, China (and 1 more)
- Hao Liu 0041 — Beihang University, School of Biological Science and Medical Engineering, Beijing, China
- Hao Liu 0042 — KU Leuven, ESAT-TELEMIC Research Division, Belgium
- Hao Liu 0043 — Dalian University of Technology, Faculty of Electronic Information and Electrical Engineering, China
- Hao Liu 0044 — Shandong University, School of Information Science and Engineering, Qingdao, China
- Hao Liu 0045 — Ocean University of China, Department of Computer Science and Technology, Qingdao, China
- Hao Liu 0046 — Guangxi Normal University, College of Electronic Engineering, China
- Hao Liu 0047 — Huazhong University of Science and Technology, School of Electrical and Electronic Engineering, State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Wuhan, China (and 1 more)
- Hao Liu 0048 — Nanjing Forestry University, China
- Hao Liu 0049 — First Institution of Oceanography, Qingdao, China
- Hao Liu 0050 — Hunan University, Department of Applied Physics, School of Physics and Electronics, Changsha, China
- Hao Liu 0051 — China University of Geosciences, School of Computer Sciences, Wuhan, China
- Hao Liu 0052 — Hangzhou Dianzi University, MOE Key Laboratory of RF Circuits and Systems, Zhejiang, China
- Hao Liu 0053 — Beijing University of Posts and Telecommunications, School of Electronic Engineering, China
- Hao Liu 0055 — University of California, Berkeley, CA, USA
- Hao Liu 0056 — Huazhong Agricultural University, Wuhan, Hubei, China (and 1 more)
- Hao Liu 0057 — Washington University in St. Louis (WashU), St. Louis, MO, USA
- Hao Liu 0058 — Guangzhou University, Cyberspace Institute of Advanced Technology, China
- Hao Liu 0059 — Xi'an Jiaotong University, School of Information and Communication Engineering, China
- Hao Liu 0060 — Changzhou University, School of Computer Science and Artifical Intelligence, China (and 1 more)
- Hao Liu 0061 — Nanyang Technological University, School of Computer Science and Engineering, Singapore (and 2 more)
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Journal Articles
- 2023
[j10]Abigail Newbury, Hao Liu, Betina Ross S. Idnay, Chunhua Weng:
The suitability of UMLS and SNOMED-CT for encoding outcome concepts. J. Am. Medical Informatics Assoc. 30(12): 1895-1903 (2023)- [j9]Yilu Fang, Hao Liu, Betina Ross S. Idnay, Casey N. Ta, Karen Marder, Chunhua Weng:
A data-driven approach to optimizing clinical study eligibility criteria. J. Biomed. Informatics 142: 104375 (2023) - 2022
- [j8]Yilu Fang, Betina Ross S. Idnay, Yingcheng Sun, Hao Liu, Zhehuan Chen, Karen Marder, Hua Xu, Rebecca Schnall, Chunhua Weng:
Combining human and machine intelligence for clinical trial eligibility querying. J. Am. Medical Informatics Assoc. 29(7): 1161-1171 (2022) - [j7]Hao Liu, Simona Carini, Zhehuan Chen, Spencer Phillips Hey, Ida Sim, Chunhua Weng:
Ontology-based categorization of clinical studies by their conditions. J. Biomed. Informatics 135: 104235 (2022) - 2021
- [j6]Yingcheng Sun, Alex M. Butler, Ibrahim Diallo, Jae Hyun Kim, Casey N. Ta, James R. Rogers, Hao Liu, Chunhua Weng:
A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data. Appl. Clin. Inform. 12(4): 816-825 (2021) - [j5]Jae Hyun Kim, Casey N. Ta, Cong Liu, Cynthia Sung, Alex M. Butler, Latoya A. Stewart, Lyudmila Ena, James R. Rogers, Junghwan Lee, Anna Ostropolets, Patrick B. Ryan, Hao Liu, Shing M. Lee, Mitchell S. V. Elkind, Chunhua Weng:
Towards clinical data-driven eligibility criteria optimization for interventional COVID-19 clinical trials. J. Am. Medical Informatics Assoc. 28(1): 14-22 (2021) - [j4]Yingcheng Sun, Alex M. Butler, Fengyang Lin, Hao Liu, Latoya A. Stewart, Jae Hyun Kim, Betina Ross S. Idnay, Qingyin Ge, Xinyi Wei, Cong Liu, Chi Yuan, Chunhua Weng:
The COVID-19 Trial Finder. J. Am. Medical Informatics Assoc. 28(3): 616-621 (2021) - [j3]Lauren Franks, Hao Liu, Mitchell S. V. Elkind, Muredach P. Reilly, Chunhua Weng, Shing M. Lee:
Misalignment between COVID-19 hotspots and clinical trial sites. J. Am. Medical Informatics Assoc. 28(11): 2461-2466 (2021) - [j2]Hao Liu, Chi Yuan, Alex M. Butler, Yingcheng Sun, Chunhua Weng:
A knowledge base of clinical trial eligibility criteria. J. Biomed. Informatics 117: 103771 (2021) - [j1]Yingcheng Sun, Alex M. Butler, Latoya A. Stewart, Hao Liu, Chi Yuan, Christopher T. Southard, Jae Hyun Kim, Chunhua Weng:
Building an OMOP common data model-compliant annotated corpus for COVID-19 clinical trials. J. Biomed. Informatics 118: 103790 (2021)
Conference and Workshop Papers
- 2024
- [c11]Jyoti Yadav, Aparna S. Varde, Hao Liu, George Antoniou, Lei Xie:
Audiovisual Multimodal Cough Data Analysis for Tuberculosis Detection. IISA 2024: 1-8 - 2023
- [c10]Hao Liu, Yifan Peng, Chunhua Weng:
How Good Is ChatGPT for Medication Evidence Synthesis? MIE 2023: 1062-1066 - 2022
- [c9]Betina Ross S. Idnay, Yilu Fang, Yingcheng Sun, Hao Liu, Zhehuan Chen, Rebecca Schnall, Chunhua Weng:
Criteria2Query 2.0: Combining Machine Efficiency and Human Intelligence to Define a More Accurate and Feasible Cohort for Clinical Trial Recruitment. AMIA 2022 - [c8]Zhehuan Chen, Yilu Fang, Hao Liu, Chunhua Weng:
Data-Driven Modeling of Randomized Controlled Trial Outcomes. MIE 2022: 392-396 - 2021
- [c7]Ali Turfah, Hao Liu, Latoya A. Stewart, Tian Kang, Chunhua Weng:
Extending PICO with Observation Normalization for Evidence Computing. MedInfo 2021: 268-272 - [c6]Cong Liu, Hao Liu, Casey N. Ta, James Roger, Alex Butler, Junghwan Lee, Jaehyun Kim, Ning Shang, Chunhua Weng:
Evaluation of Criteria2Query: Towards Augmented Intelligence for Cohort Identification. MedInfo 2021: 297-300 - [c5]Zhehuan Chen, Hao Liu, Stan Liao, Marguerite Bernard, Tian Kang, Latoya A. Stewart, Chunhua Weng:
Representation and Normalization of Complex Interventions for Evidence Computing. MedInfo 2021: 592-596 - [c4]Fengyang Lin, Hao Liu, Paul Moon, Chunhua Weng:
A Sample Size Extractor for RCT Reports. MedInfo 2021: 617-621 - [c3]Zhehuan Chen, Hao Liu, Alex M. Butler, Anna Ostropolets, Chunhua Weng:
Potential Role of Clinical Trial Eligibility Criteria in Electronic Phenotyping. MIE 2021: 148-152 - [c2]Yilu Fang, Jae Hyun Kim, Betina Ross S. Idnay, Rebeca Aragon Garcia, Carmen E. Castillo, Yingcheng Sun, Hao Liu, Cong Liu, Chi Yuan, Chunhua Weng:
Participatory Design of a Clinical Trial Eligibility Criteria Simplification Method. MIE 2021: 984-988 - 2020
- [c1]Hao Liu, Chi Yuan, Alex M. Butler, Yingcheng Sun, Chunhua Weng:
Potential Role of Clinical Trial Eligibility Criteria in Electronic Phenotyping. AMIA 2020
Data and Artifacts
- 2022
- [d18]Yasser Abduallah, Vania K. Jordanova, Hao Liu, Qin Li, Jason T. L. Wang, Haimin Wang:
Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. Version v1.2. Zenodo, 2022 [all versions]
- [d17]Yasser Abduallah, Vania K. Jordanova, Hao Liu, Qin Li, Jason T. L. Wang, Haimin Wang:
Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. Version v1.3. Zenodo, 2022 [all versions] - [d16]Yasser Abduallah, Vania K. Jordanova, Hao Liu, Qin Li, Jason T. L. Wang, Haimin Wang:
Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. Version v1.4. Zenodo, 2022 [all versions] - [d15]Yasser Abduallah, Vania K. Jordanova, Hao Liu, Qin Li, Jason T. L. Wang, Haimin Wang:
Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. Version v1.4. Zenodo, 2022 [all versions] - [d14]Yasser Abduallah, Vania K. Jordanova, Hao Liu, Qin Li, Jason T. L. Wang, Haimin Wang:
Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. Version v1.4. Zenodo, 2022 [all versions] - [d13]Yasser Abduallah, Vania K. Jordanova, Hao Liu, Qin Li, Jason T. L. Wang, Haimin Wang:
Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. Version v1.4. Zenodo, 2022 [all versions] - [d12]Yasser Abduallah, Vania K. Jordanova, Hao Liu, Qin Li, Jason T. L. Wang, Haimin Wang:
Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. Version v1.4. Zenodo, 2022 [all versions] - [d11]Hao Liu, Chang Liu, Jason T. L. Wang, Haimin Wang:
Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks. Version v1.3. Zenodo, 2022 [all versions] - 2021
- [d10]Haodi Jiang, Jiasheng Wang, Chang Liu, Ju Jing, Hao Liu, Jason T. L. Wang, Haimin Wang:
Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning. Version v1.0.1. Zenodo, 2021 [all versions] - [d9]Haodi Jiang, Jiasheng Wang, Chang Liu, Ju Jing, Hao Liu, Jason T. L. Wang, Haimin Wang:
Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning. Version v1.0.2. Zenodo, 2021 [all versions] - [d8]Haodi Jiang, Jiasheng Wang, Chang Liu, Ju Jing, Hao Liu, Jason T. L. Wang, Haimin Wang:
Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning. Version v.1.2. Zenodo, 2021 [all versions] - [d7]Hao Liu, Chang Liu, Jason T. L. Wang, Haimin Wang:
Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks. Version v1.0.1. Zenodo, 2021 [all versions] - [d6]Hao Liu, Chang Liu, Jason T. L. Wang, Haimin Wang:
Predicting Solar Flares Using a Long Short-term Memory Network. Version v1.0.1. Zenodo, 2021 [all versions] - [d5]Hao Liu, Chang Liu, Jason T. L. Wang, Haimin Wang:
Predicting Solar Flares Using a Long Short-term Memory Network. Version v1.0.2. Zenodo, 2021 [all versions] - [d4]Hao Liu, Chang Liu, Jason T. L. Wang, Haimin Wang:
Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks. Version v1.0.2. Zenodo, 2021 [all versions] - 2019
- [d3]Hao Liu, Chang Liu, Jason Tsong-Li Wang, Haimin Wang:
Predicting Solar Flares Using a Long Short-term Memory Network. Zenodo, 2019 - [d2]Hao Liu, Chang Liu, Jason Tsong-Li Wang, Haimin Wang:
Predicting Solar Flares Using a Long Short-term Memory Network. Version v1.0.0. Zenodo, 2019 [all versions] - [d1]Hao Liu, Chang Liu, Jason Tsong-Li Wang, Haimin Wang:
Prism2/LSTM-flare-prediction: v1.0.1. Version v1.0.1. Zenodo, 2019 [all versions]
Informal and Other Publications
- 2025
- [i1]Blessing Austin-Gabriel, Aparna S. Varde, Hao Liu:
Geoinformatics-Guided Machine Learning for Power Plant Classification. CoRR abs/2502.01039 (2025)
Coauthor Index
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