Zongcheng Ji
- Artificial Intelligence top 2%
- Molecular Biology
- Information Systems top 5%
- Computer Science Applications top 5%
- Health Information Management top 2%
- Topics
- Topic Modeling (18 papers)Natural Language Processing Techniques (12 papers)Biomedical Text Mining and Ontologies (9 papers)
- Journals
- IEEE Transactions on Knowledge and Data EngineeringJournal of the American Medical Informatics AssociationInformation Processing & Management
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Zongcheng Ji
23 papers receiving 731 citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Artificial Intelligence 547
- Molecular Biology 253
- Information Systems 167
- Computer Science Applications 78
- Health Information Management 72
Countries citing papers authored by Zongcheng Ji
This map shows the geographic impact of Zongcheng Ji's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zongcheng Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zongcheng Ji more than expected).
Fields of papers citing papers by Zongcheng Ji
This network shows the impact of papers produced by Zongcheng Ji. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zongcheng Ji. The network helps show where Zongcheng Ji may publish in the future.
Co-authorship network of co-authors of Zongcheng Ji
This figure shows the co-authorship network connecting the top 25 collaborators of Zongcheng Ji. A scholar is included among the top collaborators of Zongcheng Ji based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zongcheng Ji. Zongcheng Ji is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 2 | |
| 5 | 6 | |
| 6 | A Discrete Joint Model for Entity and Relation Extraction from Clinical Notes. | 2 |
| 7 | 2 | |
| 8 | 6 | |
| 9 | 28 | |
| 10 | BERT-based Ranking for Biomedical Entity Normalization. | 42 |
| 11 | Cost-sensitive Active Learning for Phenotyping of Electronic Health Records. | 5 |
| 12 | Deep learning in clinical natural language processing: a methodical reviewbreakdown → | 291 |
| 13 | 85 | |
| 14 | 16 | |
| 15 | Relation Extraction from Clinical Narratives Using Pre-trained Language Models. | 29 |
| 16 | UTH_CCB System for Adverse Drug Reaction Extraction from Drug Labels at TAC-ADR 2017. | 14 |
| 17 | 10 | |
| 18 | 2 | |
| 19 | 37 | |
| 20 | 38 |
About Zongcheng Ji
Zongcheng Ji is a scholar working on Artificial Intelligence, Toxicology and Health Information Management, having authored 25 papers that have together received 760 indexed citations. Recurring topics across this work include Topic Modeling (18 papers), Natural Language Processing Techniques (12 papers) and Biomedical Text Mining and Ontologies (9 papers). The work is most often cited by research in Health Informatics (55 citations), Artificial Intelligence (547 citations) and Health Information Management (72 citations). Zongcheng Ji has collaborated with scholars based in China, United States and France. Frequent co-authors include Hua Xu, Bin Wang, Qiang Wei, Stephen Wu, Fei Xu, Jingcheng Du, Yang Xiang, Kirk Roberts, Yuqi Si and Qiong Wang. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Journal of the American Medical Informatics Association and Information Processing & Management.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.