Qika Lin

1.3k citations
39 papers · 712 · 1 hit paper · h-index 17

Impact in

    • Topic Modeling
    • Advanced Graph Neural Networks
    • Natural Language Processing Techniques
    • Sentiment Analysis and Opinion Mining
    • Machine Learning in Healthcare

Papers in

Qika Lin

34 papers receiving 693 citations

Qika Lin's Hit Papers

A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics 2025 · 41 citations
410Years since publication10203040

Peers

Qika Lin
Comparison fields: 5 of 89
  • Health Informatics 24
  • Artificial Intelligence 483
  • Management Science and Operations Research 125
  • Computer Science Applications 45
  • Information Systems 139
Replace Daochen Zha with:
Daochen Zha United States
Yunyao Li United States
Tyler Derr United States
Jack Wu Hong Kong
Lucian Popa United States
Nico Schlaefer United States
Marina Danilevsky United States
Stephen H. Bach United States
Chuanqi Tan China
Qika Lin relative to Daochen Zha United States Daochen Zha's profile →
Citations per field
00.5×4.1×
Daochen Zha · 1×
Citations per year

Countries citing papers authored by Qika Lin

Since Specialization
Citations

This map shows the geographic impact of Qika Lin'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 Qika Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qika Lin more than expected).

Fields of papers citing papers by Qika Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Qika Lin. 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 Qika Lin. The network helps show where Qika Lin may publish in the future.

Co-authors

The 25 scholars most cited alongside Qika Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Qika Lin Line = papers co-authored together Qika Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202277
2 201853
3 202249
4 202148
5
A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics
Hit paper breakdown →
202541
6 202434
7 201834
8 202231
9 202331
10 202328
11 202128
12 202327
13 201926
14 202124
15 202224
16 202023
17 202123
18 202516
19 202112
20 202212

About Qika Lin

Qika Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Management Science and Operations Research and Computer Science Applications, having authored 39 papers that have together received 712 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (18 papers), Topic Modeling (15 papers), Natural Language Processing Techniques (6 papers), Multimodal Machine Learning Applications (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), Online Learning and Analytics (3 papers), Sentiment Analysis and Opinion Mining (3 papers) and Recommender Systems and Techniques (3 papers). The work is most often cited by research in Health Informatics (24 citations), Artificial Intelligence (483 citations), Management Science and Operations Research (125 citations), Computer Science Applications (45 citations) and Information Systems (139 citations). Qika Lin has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Erik Cambria, Yifan Zhu, Rui Mao, Zhendong Niu, Jun Liu, Hao Lü, Peng Wu, Lingling Zhang, Kaize Shi and Pengfei Shi. Their work appears in journals such as Information Fusion, IEEE Transactions on Knowledge and Data Engineering, IEEE Access, IEEE Transactions on Neural Networks and Learning Systems and Information Sciences.

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.

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